{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T19:22:58Z","timestamp":1776194578223,"version":"3.50.1"},"reference-count":254,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2023,3,1]],"date-time":"2023-03-01T00:00:00Z","timestamp":1677628800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,3,1]],"date-time":"2023-03-01T00:00:00Z","timestamp":1677628800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T00:00:00Z","timestamp":1667433600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61902054"],"award-info":[{"award-number":["61902054"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62002047"],"award-info":[{"award-number":["62002047"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62027827"],"award-info":[{"award-number":["62027827"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072074"],"award-info":[{"award-number":["62072074"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62076054"],"award-info":[{"award-number":["62076054"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005408","name":"University of Electronic Science and Technology of China","doi-asserted-by":"publisher","award":["ZYGX2021YGLH212"],"award-info":[{"award-number":["ZYGX2021YGLH212"]}],"id":[{"id":"10.13039\/501100005408","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005408","name":"University of Electronic Science and Technology of China","doi-asserted-by":"publisher","award":["ZYGX2022YGRH012"],"award-info":[{"award-number":["ZYGX2022YGRH012"]}],"id":[{"id":"10.13039\/501100005408","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Fusion"],"published-print":{"date-parts":[[2023,3]]},"DOI":"10.1016\/j.inffus.2022.10.032","type":"journal-article","created":{"date-parts":[[2022,11,7]],"date-time":"2022-11-07T02:17:03Z","timestamp":1667787423000},"page":"694-712","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":65,"special_numbering":"C","title":["A survey of identity recognition via data fusion and feature learning"],"prefix":"10.1016","volume":"91","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7857-9719","authenticated-orcid":false,"given":"Zhen","family":"Qin","sequence":"first","affiliation":[]},{"given":"Pengbiao","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Tianming","family":"Zhuang","sequence":"additional","affiliation":[]},{"given":"Fuhu","family":"Deng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3406-9770","authenticated-orcid":false,"given":"Yi","family":"Ding","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0745-5836","authenticated-orcid":false,"given":"Dajiang","family":"Chen","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.inffus.2022.10.032_b1","series-title":"Handbook of Face Recognition","author":"Jain","year":"2011"},{"key":"10.1016\/j.inffus.2022.10.032_b2","series-title":"Handbook of Iris Recognition","author":"Bowyer","year":"2016"},{"key":"10.1016\/j.inffus.2022.10.032_b3","series-title":"Handbook of Fingerprint Recognition","author":"Maltoni","year":"2009"},{"key":"10.1016\/j.inffus.2022.10.032_b4","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.inffus.2018.12.003","article-title":"A comprehensive overview of biometric fusion","volume":"52","author":"Singh","year":"2019","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.inffus.2022.10.032_b5","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/j.inffus.2021.06.007","article-title":"A comprehensive survey on multimodal medical signals fusion for smart healthcare systems","volume":"76","author":"Muhammad","year":"2021","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.inffus.2022.10.032_b6","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.inffus.2017.02.006","article-title":"Biometric information fusion for web user navigation and preferences analysis: An overview","volume":"38","author":"Slanzi","year":"2017","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.inffus.2022.10.032_b7","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.inffus.2021.10.018","article-title":"Multi-modal bioelectrical signal fusion analysis based on different acquisition devices and scene settings: Overview, challenges, and novel orientation","volume":"79","author":"Li","year":"2022","journal-title":"Inf. Fusion"},{"issue":"6","key":"10.1016\/j.inffus.2022.10.032_b8","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1109\/MSP.2017.2738401","article-title":"Deep multimodal learning: A survey on recent advances and trends","volume":"34","author":"Ramachandram","year":"2017","journal-title":"IEEE Signal Process. Mag."},{"key":"10.1016\/j.inffus.2022.10.032_b9","series-title":"2015 IEEE\/ACIS 14th International Conference on Computer and Information Science","first-page":"131","article-title":"A review of multimodal biometric systems: Fusion methods and their applications","author":"Ghayoumi","year":"2015"},{"key":"10.1016\/j.inffus.2022.10.032_b10","series-title":"2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld\/SCALCOM\/UIC\/ATC\/CBDCom\/IOP\/SCI)","first-page":"1997","article-title":"A review of multimodal facial biometric authentication methods in mobile devices and their application in head mounted displays","author":"Olade","year":"2018"},{"key":"10.1016\/j.inffus.2022.10.032_b11","doi-asserted-by":"crossref","DOI":"10.1109\/ACCESS.2021.3061589","article-title":"Continuous multimodal biometric authentication schemes: a systematic review","author":"Ryu","year":"2021","journal-title":"IEEE Access"},{"key":"10.1016\/j.inffus.2022.10.032_b12","series-title":"2019 3rd International Conference on Trends in Electronics and Informatics","first-page":"1062","article-title":"Multimodal biometric authentication with secured templates\u2014A review","author":"Choudhary","year":"2019"},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b13","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1007\/BF01421486","article-title":"Visual learning and recognition of 3-D objects from appearance","volume":"14","author":"Murase","year":"1995","journal-title":"Int. J. Comput. Vis."},{"issue":"6","key":"10.1016\/j.inffus.2022.10.032_b14","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1109\/34.927467","article-title":"Active appearance models","volume":"23","author":"Cootes","year":"2001","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2022.10.032_b15","series-title":"2009 Third International Symposium on Intelligent Information Technology Application Workshops","first-page":"348","article-title":"Face recognition using constrained active appearance model","author":"Weiwei","year":"2009"},{"key":"10.1016\/j.inffus.2022.10.032_b16","series-title":"2013 18th International Conference on Digital Signal Processing","first-page":"1","article-title":"Multi-model AAM framework for face image modeling","author":"Khan","year":"2013"},{"issue":"8","key":"10.1016\/j.inffus.2022.10.032_b17","doi-asserted-by":"crossref","first-page":"857","DOI":"10.1016\/j.imavis.2006.02.009","article-title":"3D shape-based face representation and feature extraction for face recognition","volume":"24","author":"G\u00f6kberk","year":"2006","journal-title":"Image Vis. Comput."},{"key":"10.1016\/j.inffus.2022.10.032_b18","series-title":"International Conference on Biometrics","first-page":"99","article-title":"3D face recognition based on facial shape indexes with dynamic programming","author":"Song","year":"2006"},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b19","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1109\/TSMCB.2007.908865","article-title":"Representation plurality and fusion for 3-D face recognition","volume":"38","author":"Gokberk","year":"2008","journal-title":"IEEE Trans. Syst. Man Cybern. B"},{"key":"10.1016\/j.inffus.2022.10.032_b20","series-title":"2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR\u201905)","first-page":"886","article-title":"Histograms of oriented gradients for human detection","volume":"1","author":"Dalal","year":"2005"},{"issue":"12","key":"10.1016\/j.inffus.2022.10.032_b21","doi-asserted-by":"crossref","first-page":"1598","DOI":"10.1016\/j.patrec.2011.01.004","article-title":"Face recognition using histograms of oriented gradients","volume":"32","author":"D\u00e9niz","year":"2011","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.inffus.2022.10.032_b22","series-title":"2012 IEEE International Conference on Acoustics, Speech and Signal Processing","first-page":"1301","article-title":"Face recognition using co-occurrence histograms of oriented gradients","author":"Do","year":"2012"},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b23","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/0031-3203(95)00067-4","article-title":"A comparative study of texture measures with classification based on featured distributions","volume":"29","author":"Ojala","year":"1996","journal-title":"Pattern Recognit."},{"issue":"2","key":"10.1016\/j.inffus.2022.10.032_b24","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive image features from scale-invariant keypoints","volume":"60","author":"Lowe","year":"2004","journal-title":"Int. J. Comput. Vis."},{"issue":"6","key":"10.1016\/j.inffus.2022.10.032_b25","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1109\/TSMCC.2011.2118750","article-title":"Local binary patterns and its application to facial image analysis: a survey","volume":"41","author":"Huang","year":"2011","journal-title":"IEEE Trans. Syst. Man. Cybern. C"},{"issue":"05","key":"10.1016\/j.inffus.2022.10.032_b26","doi-asserted-by":"crossref","DOI":"10.1142\/S0218001412660024","article-title":"Face recognition from video: A review","volume":"26","author":"Barr","year":"2012","journal-title":"Int. J. Pattern Recognit. Artif. Intell."},{"issue":"4","key":"10.1016\/j.inffus.2022.10.032_b27","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.1109\/TPAMI.2017.2700390","article-title":"Trunk-branch ensemble convolutional neural networks for video-based face recognition","volume":"40","author":"Ding","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"3","key":"10.1016\/j.inffus.2022.10.032_b28","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1109\/TIFS.2018.2866295","article-title":"Domain-specific face synthesis for video face recognition from a single sample per person","volume":"14","author":"Mokhayeri","year":"2018","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"10.1016\/j.inffus.2022.10.032_b29","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2019.107129","article-title":"A paired sparse representation model for robust face recognition from a single sample","volume":"100","author":"Mokhayeri","year":"2020","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.inffus.2022.10.032_b30","doi-asserted-by":"crossref","unstructured":"W. Wang, R. Wang, Z. Huang, S. Shan, X. Chen, Discriminant analysis on Riemannian manifold of Gaussian distributions for face recognition with image sets, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 2048\u20132057.","DOI":"10.1109\/CVPR.2015.7298816"},{"key":"10.1016\/j.inffus.2022.10.032_b31","series-title":"2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018)","first-page":"621","article-title":"Changes in facial expression as biometric: a database and benchmarks of identification","author":"Haamer","year":"2018"},{"key":"10.1016\/j.inffus.2022.10.032_b32","series-title":"2016 IEEE International Conference on Image Processing","first-page":"2996","article-title":"Spatio-temporal representation for face authentication by using multi-task learning with human attributes","author":"Kim","year":"2016"},{"issue":"6","key":"10.1016\/j.inffus.2022.10.032_b33","doi-asserted-by":"crossref","first-page":"970","DOI":"10.1109\/THMS.2017.2681425","article-title":"Dynamic texture comparison using derivative sparse representation: Application to video-based face recognition","volume":"47","author":"Hajati","year":"2017","journal-title":"IEEE Trans. Hum.-Mach. Syst."},{"key":"10.1016\/j.inffus.2022.10.032_b34","series-title":"Proceedings of IEEE International Conference on Computer Vision","first-page":"694","article-title":"Geodesic active contours","author":"Caselles","year":"1995"},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b35","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1023\/A:1007979827043","article-title":"Geodesic active contours","volume":"22","author":"Caselles","year":"1997","journal-title":"Int. J. Comput. Vis."},{"issue":"11","key":"10.1016\/j.inffus.2022.10.032_b36","doi-asserted-by":"crossref","first-page":"564","DOI":"10.3844\/jcssp.2016.564.571","article-title":"Implementation of geodesic active contour approach for pigment spots segmentation on the iris surface","volume":"12","author":"Mustafa","year":"2016","journal-title":"J. Comput. Sci."},{"key":"10.1016\/j.inffus.2022.10.032_b37","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.cogsys.2018.09.029","article-title":"Reliable pupil detection and iris segmentation algorithm based on SPS","volume":"57","author":"Susitha","year":"2019","journal-title":"Cogn. Syst. Res."},{"issue":"5","key":"10.1016\/j.inffus.2022.10.032_b38","doi-asserted-by":"crossref","first-page":"1089","DOI":"10.1007\/s11554-019-00859-w","article-title":"Real-time iris segmentation and its implementation on FPGA","volume":"17","author":"Khan","year":"2020","journal-title":"J. Real-Time Image Process."},{"key":"10.1016\/j.inffus.2022.10.032_b39","doi-asserted-by":"crossref","first-page":"85082","DOI":"10.1109\/ACCESS.2019.2924464","article-title":"A robust iris segmentation scheme based on improved U-net","volume":"7","author":"Zhang","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.inffus.2022.10.032_b40","doi-asserted-by":"crossref","first-page":"123959","DOI":"10.1109\/ACCESS.2019.2938809","article-title":"Study on iris segmentation algorithm based on dense U-net","volume":"7","author":"Wu","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.inffus.2022.10.032_b41","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1016\/j.jvcir.2018.10.001","article-title":"Attention guided U-net for accurate iris segmentation","volume":"56","author":"Lian","year":"2018","journal-title":"J. Vis. Commun. Image Represent."},{"key":"10.1016\/j.inffus.2022.10.032_b42","series-title":"2017 13th International Conference on Signal-Image Technology & Internet-Based Systems","first-page":"184","article-title":"IpSegNet: deep convolutional neural network based segmentation framework for iris and pupil","author":"Patil","year":"2017"},{"issue":"4","key":"10.1016\/j.inffus.2022.10.032_b43","doi-asserted-by":"crossref","first-page":"652","DOI":"10.1134\/S1054661818040193","article-title":"Iris segmentation in challenging conditions","volume":"28","author":"Korobkin","year":"2018","journal-title":"Pattern Recognit. Image Anal."},{"key":"10.1016\/j.inffus.2022.10.032_b44","series-title":"2018 IEEE International Work Conference on Bioinspired Intelligence","first-page":"1","article-title":"Deep multi-class eye segmentation for ocular biometrics","author":"Rot","year":"2018"},{"key":"10.1016\/j.inffus.2022.10.032_b45","series-title":"2016 International Conference on Biometrics","first-page":"1","article-title":"Accurate iris segmentation in non-cooperative environments using fully convolutional networks","author":"Liu","year":"2016"},{"key":"10.1016\/j.inffus.2022.10.032_b46","series-title":"Chinese Conference on Biometric Recognition","first-page":"428","article-title":"Visible spectral iris segmentation via deep convolutional network","author":"He","year":"2017"},{"key":"10.1016\/j.inffus.2022.10.032_b47","series-title":"Geoinformatics 2007: Geospatial Information Science","first-page":"67532F","article-title":"SIFT based iris feature extraction and matching","volume":"6753","author":"Geng","year":"2007"},{"key":"10.1016\/j.inffus.2022.10.032_b48","series-title":"International Conference on Biometrics","first-page":"1080","article-title":"Efficient iris spoof detection via boosted local binary patterns","author":"He","year":"2009"},{"key":"10.1016\/j.inffus.2022.10.032_b49","series-title":"2010 20th International Conference on Pattern Recognition","first-page":"4279","article-title":"Contact lens detection based on weighted LBP","author":"Zhang","year":"2010"},{"key":"10.1016\/j.inffus.2022.10.032_b50","series-title":"2nd International Workshop on Biometrics and Forensics","first-page":"1","article-title":"Binarized statistical features for improved iris and periocular recognition in visible spectrum","author":"Raja","year":"2014"},{"key":"10.1016\/j.inffus.2022.10.032_b51","series-title":"2008 23rd International Symposium on Computer and Information Sciences","first-page":"1","article-title":"Iris recognition system using combined histogram statistics","author":"Demirel","year":"2008"},{"key":"10.1016\/j.inffus.2022.10.032_b52","doi-asserted-by":"crossref","first-page":"18848","DOI":"10.1109\/ACCESS.2017.2784352","article-title":"Iris recognition with off-the-shelf CNN features: A deep learning perspective","volume":"6","author":"Nguyen","year":"2017","journal-title":"IEEE Access"},{"issue":"4","key":"10.1016\/j.inffus.2022.10.032_b53","doi-asserted-by":"crossref","first-page":"864","DOI":"10.1109\/TIFS.2015.2398817","article-title":"Deep representations for iris, face, and fingerprint spoofing detection","volume":"10","author":"Menotti","year":"2015","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"10.1016\/j.inffus.2022.10.032_b54","series-title":"2nd International Workshop on Biometrics and Forensics","first-page":"1","article-title":"Integrating ocular and iris descriptors for fake iris image detection","author":"Tan","year":"2014"},{"key":"10.1016\/j.inffus.2022.10.032_b55","series-title":"2015 28th SIBGRAPI Conference on Graphics, Patterns and Images","first-page":"157","article-title":"An approach to iris contact lens detection based on deep image representations","author":"Silva","year":"2015"},{"key":"10.1016\/j.inffus.2022.10.032_b56","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.patrec.2018.12.003","article-title":"Iris recognition in visible spectrum based on multi-layer analogous convolution and collaborative representation","volume":"117","author":"Liu","year":"2019","journal-title":"Pattern Recognit. Lett."},{"issue":"2","key":"10.1016\/j.inffus.2022.10.032_b57","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1016\/j.eswa.2013.07.083","article-title":"Iris recognition using combined support vector machine and hamming distance approach","volume":"41","author":"Rai","year":"2014","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.inffus.2022.10.032_b58","series-title":"2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems","first-page":"1","article-title":"Automated classification of mislabeled near-infrared left and right iris images using convolutional neural networks","author":"Du","year":"2016"},{"key":"10.1016\/j.inffus.2022.10.032_b59","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.patrec.2017.04.010","article-title":"A deep learning approach for iris sensor model identification","volume":"113","author":"Marra","year":"2018","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.inffus.2022.10.032_b60","doi-asserted-by":"crossref","unstructured":"Z. Zhao, A. Kumar, Towards more accurate iris recognition using deeply learned spatially corresponding features, in: Proceedings of the IEEE International Conference on Computer Vision, 2017, pp. 3809\u20133818.","DOI":"10.1109\/ICCV.2017.411"},{"key":"10.1016\/j.inffus.2022.10.032_b61","series-title":"Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications","first-page":"69","article-title":"Person recognition with modular deep neural network using the iris biometric measure","author":"Gaxiola","year":"2018"},{"key":"10.1016\/j.inffus.2022.10.032_b62","series-title":"2016 International Conference on Open Source Systems & Technologies","first-page":"72","article-title":"Deep belief networks for iris recognition based on contour detection","author":"Baqar","year":"2016"},{"issue":"2","key":"10.1016\/j.inffus.2022.10.032_b63","doi-asserted-by":"crossref","DOI":"10.1117\/1.JEI.26.2.023005","article-title":"Deep learning architecture for iris recognition based on optimal gabor filters and deep belief network","volume":"26","author":"He","year":"2017","journal-title":"J. Electron. Imaging"},{"key":"10.1016\/j.inffus.2022.10.032_b64","doi-asserted-by":"crossref","first-page":"182395","DOI":"10.1109\/ACCESS.2019.2956726","article-title":"Application of iris images in racial classifications based on dilate convolution and residual network","volume":"7","author":"Lu","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.inffus.2022.10.032_b65","series-title":"2016 International Conference on Emerging Trends in Engineering, Technology and Science","first-page":"1","article-title":"Ear detection using active contour model","author":"Deepak","year":"2016"},{"key":"10.1016\/j.inffus.2022.10.032_b66","series-title":"2008 IEEE Workshop on Applications of Computer Vision","first-page":"1","article-title":"Fast and fully automatic ear detection using cascaded adaboost","author":"Islam","year":"2008"},{"key":"10.1016\/j.inffus.2022.10.032_b67","series-title":"2009 International Conference on Machine Learning and Cybernetics","first-page":"2414","article-title":"Ear detection based on improved adaboost algorithm","volume":"4","author":"Yuan","year":"2009"},{"key":"10.1016\/j.inffus.2022.10.032_b68","series-title":"2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems","first-page":"1","article-title":"Fast learning ear detection for real-time surveillance","author":"Abaza","year":"2010"},{"key":"10.1016\/j.inffus.2022.10.032_b69","series-title":"2009 16th IEEE International Conference on Image Processing","first-page":"2741","article-title":"Connected component based technique for automatic ear detection","author":"Prakash","year":"2009"},{"key":"10.1016\/j.inffus.2022.10.032_b70","series-title":"Optics and Photonics in Global Homeland Security V and Biometric Technology for Human Identification VI","first-page":"361","article-title":"Ear localization using hierarchical clustering","volume":"7306","author":"Prakash","year":"2009"},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b71","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.imavis.2011.11.005","article-title":"An efficient ear localization technique","volume":"30","author":"Prakash","year":"2012","journal-title":"Image Vis. Comput."},{"key":"10.1016\/j.inffus.2022.10.032_b72","series-title":"2007 International Conference on Computing: Theory and Applications (ICCTA\u201907)","first-page":"688","article-title":"Localization of ear using outer helix curve of the ear","author":"Ansari","year":"2007"},{"key":"10.1016\/j.inffus.2022.10.032_b73","series-title":"2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems","first-page":"1","article-title":"Histograms of categorized shapes for 3D ear detection","author":"Zhou","year":"2010"},{"key":"10.1016\/j.inffus.2022.10.032_b74","series-title":"2012 IEEE International Carnahan Conference on Security Technology","first-page":"90","article-title":"Towards making HCS ear detection robust against rotation","author":"Pflug","year":"2012"},{"key":"10.1016\/j.inffus.2022.10.032_b75","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.engappai.2013.07.022","article-title":"Entropy based binary particle swarm optimization and classification for ear detection","volume":"27","author":"Ganesh","year":"2014","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"2","key":"10.1016\/j.inffus.2022.10.032_b76","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1007\/s00138-015-0669-y","article-title":"Entropy-cum-hough-transform-based ear detection using ellipsoid particle swarm optimization","volume":"26","author":"Chidananda","year":"2015","journal-title":"Mach. Vis. Appl."},{"issue":"2","key":"10.1016\/j.inffus.2022.10.032_b77","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1109\/TSMC.2015.2452892","article-title":"Automatic ear landmark localization, segmentation, and pose classification in range images","volume":"46","author":"Lei","year":"2015","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"10.1016\/j.inffus.2022.10.032_b78","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1016\/j.neucom.2015.06.074","article-title":"Non-negative dictionary based sparse representation classification for ear recognition with occlusion","volume":"171","author":"Yuan","year":"2016","journal-title":"Neurocomputing"},{"key":"10.1016\/j.inffus.2022.10.032_b79","series-title":"2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems","first-page":"278","article-title":"Ear recognition via sparse representation and gabor filters","author":"Khorsandi","year":"2012"},{"key":"10.1016\/j.inffus.2022.10.032_b80","series-title":"2013 IEEE Workshop on Applications of Computer Vision","first-page":"461","article-title":"Gender classification using 2-D ear images and sparse representation","author":"Khorsandi","year":"2013"},{"key":"10.1016\/j.inffus.2022.10.032_b81","series-title":"2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems","first-page":"1","article-title":"Robust biometrics recognition using joint weighted dictionary learning and smoothed L0 norm","author":"Khorsandi","year":"2015"},{"key":"10.1016\/j.inffus.2022.10.032_b82","series-title":"The 26th Chinese Control and Decision Conference (2014 CCDC)","first-page":"4410","article-title":"Ear recognition based on weighted wavelet transform and DCT","author":"Ying","year":"2014"},{"key":"10.1016\/j.inffus.2022.10.032_b83","series-title":"2014 6th IEEE Power India International Conference","first-page":"1","article-title":"A new gabor wavelet transform feature extraction technique for ear biometric recognition","author":"Soni","year":"2014"},{"key":"10.1016\/j.inffus.2022.10.032_b84","series-title":"2011 7th Iranian Conference on Machine Vision and Image Processing","first-page":"1","article-title":"An ear identification system using local-gabor features and knn classifier","author":"Tahmasebi","year":"2011"},{"issue":"3","key":"10.1016\/j.inffus.2022.10.032_b85","doi-asserted-by":"crossref","first-page":"956","DOI":"10.1016\/j.patcog.2011.06.005","article-title":"Automated human identification using ear imaging","volume":"45","author":"Kumar","year":"2012","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.inffus.2022.10.032_b86","series-title":"2008 19th International Conference on Pattern Recognition","first-page":"1","article-title":"Robust log-gabor filter for ear biometrics","author":"Arbab-Zavar","year":"2008"},{"key":"10.1016\/j.inffus.2022.10.032_b87","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.engappai.2013.09.014","article-title":"Optimization of modular granular neural networks using hierarchical genetic algorithms for human recognition using the ear biometric measure","volume":"27","author":"S\u00e1nchez","year":"2014","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"5","key":"10.1016\/j.inffus.2022.10.032_b88","doi-asserted-by":"crossref","first-page":"1265","DOI":"10.1007\/s00521-012-1068-1","article-title":"Ear recognition with feed-forward artificial neural networks","volume":"23","author":"Sibai","year":"2013","journal-title":"Neural Comput. Appl."},{"key":"10.1016\/j.inffus.2022.10.032_b89","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.engappai.2016.05.005","article-title":"Image set based ear recognition using novel dictionary learning and classification scheme","volume":"55","author":"Banerjee","year":"2016","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.inffus.2022.10.032_b90","series-title":"2007 First IEEE International Conference on Biometrics: Theory, Applications, and Systems","first-page":"1","article-title":"Human identification based on 3D ear models","author":"Cadavid","year":"2007"},{"key":"10.1016\/j.inffus.2022.10.032_b91","series-title":"2013 IEEE International Conference on Image Processing","first-page":"4176","article-title":"A novel shape-based interest point descriptor (SIP) for 3D ear recognition","author":"Lei","year":"2013"},{"key":"10.1016\/j.inffus.2022.10.032_b92","series-title":"2013 International Conference on Computer-Aided Design and Computer Graphics","first-page":"377","article-title":"3D ear matching using local salient shape feature","author":"Sun","year":"2013"},{"key":"10.1016\/j.inffus.2022.10.032_b93","series-title":"Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition","first-page":"755","article-title":"A novel coding scheme for indexing fingerprint patterns","author":"Gyaourova","year":"2008"},{"key":"10.1016\/j.inffus.2022.10.032_b94","series-title":"International Conference on Audio-and Video-Based Biometric Person Authentication","first-page":"436","article-title":"Practical biometric authentication with template protection","author":"Tuyls","year":"2005"},{"key":"10.1016\/j.inffus.2022.10.032_b95","series-title":"2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems","first-page":"1","article-title":"Binary feature vector fingerprint representation from minutiae vicinities","author":"Bringer","year":"2010"},{"key":"10.1016\/j.inffus.2022.10.032_b96","series-title":"Proceedings 2003 International Conference on Image Processing (Cat. No. 03CH37429)","first-page":"II","article-title":"Improved fingercode for filterbank-based fingerprint matching","volume":"2","author":"Sha","year":"2003"},{"key":"10.1016\/j.inffus.2022.10.032_b97","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"1627","article-title":"MinNet: Minutia patch embedding network for automated latent fingerprint recognition","author":"\u00d6zt\u00fcrk","year":"2022"},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b98","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1049\/el:20010031","article-title":"Wavelet domain features for fingerprint recognition","volume":"37","author":"Tico","year":"2001","journal-title":"Electron. Lett."},{"issue":"9","key":"10.1016\/j.inffus.2022.10.032_b99","doi-asserted-by":"crossref","first-page":"522","DOI":"10.1049\/el:20064330","article-title":"Fingerprint recognition using DCT features","volume":"42","author":"Amornraksa","year":"2006","journal-title":"Electron. Lett."},{"issue":"3","key":"10.1016\/j.inffus.2022.10.032_b100","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1109\/TIFS.2009.2021692","article-title":"Fingerprint verification using spectral minutiae representations","volume":"4","author":"Xu","year":"2009","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"issue":"10","key":"10.1016\/j.inffus.2022.10.032_b101","doi-asserted-by":"crossref","first-page":"1987","DOI":"10.1016\/j.patcog.2004.02.015","article-title":"Palmprint classification using principal lines","volume":"37","author":"Wu","year":"2004","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.inffus.2022.10.032_b102","series-title":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004","first-page":"475","article-title":"Palmprint recognition using directional line energy feature","volume":"4","author":"Wu","year":"2004"},{"key":"10.1016\/j.inffus.2022.10.032_b103","series-title":"IEEE International Workshop on Biomedical Circuits and Systems, 2004","first-page":"S3","article-title":"Palmprint identification using hausdorff distance","author":"Li","year":"2004"},{"issue":"4","key":"10.1016\/j.inffus.2022.10.032_b104","doi-asserted-by":"crossref","first-page":"1316","DOI":"10.1016\/j.patcog.2007.08.016","article-title":"Palmprint verification based on principal lines","volume":"41","author":"Huang","year":"2008","journal-title":"Pattern Recognit."},{"issue":"6","key":"10.1016\/j.inffus.2022.10.032_b105","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","article-title":"A computational approach to edge detection","volume":"PAMI-8","author":"Canny","year":"1986","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"2","key":"10.1016\/j.inffus.2022.10.032_b106","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1007\/s10044-005-0006-6","article-title":"Fusion of phase and orientation information for palmprint authentication","volume":"9","author":"Wu","year":"2006","journal-title":"Pattern Anal. Appl."},{"key":"10.1016\/j.inffus.2022.10.032_b107","series-title":"2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR\u201905)","first-page":"279","article-title":"Ordinal palmprint represention for personal identification [represention read representation]","volume":"1","author":"Sun","year":"2005"},{"issue":"5","key":"10.1016\/j.inffus.2022.10.032_b108","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1016\/j.imavis.2005.01.002","article-title":"An automated palmprint recognition system","volume":"23","author":"Connie","year":"2005","journal-title":"Image Vis. Comput."},{"issue":"15","key":"10.1016\/j.inffus.2022.10.032_b109","doi-asserted-by":"crossref","first-page":"2829","DOI":"10.1016\/S0167-8655(03)00141-7","article-title":"Fisherpalms based palmprint recognition","volume":"24","author":"Wu","year":"2003","journal-title":"Pattern Recognit. Lett."},{"issue":"9\u201310","key":"10.1016\/j.inffus.2022.10.032_b110","doi-asserted-by":"crossref","first-page":"1463","DOI":"10.1016\/S0167-8655(02)00386-0","article-title":"Palmprint recognition using eigenpalms features","volume":"24","author":"Lu","year":"2003","journal-title":"Pattern Recognit. Lett."},{"issue":"3","key":"10.1016\/j.inffus.2022.10.032_b111","doi-asserted-by":"crossref","first-page":"1335","DOI":"10.1109\/TSMCB.2004.824521","article-title":"Characterization of palmprints by wavelet signatures via directional context modeling","volume":"34","author":"Zhang","year":"2004","journal-title":"IEEE Trans. Syst. Man Cybern. B"},{"issue":"11","key":"10.1016\/j.inffus.2022.10.032_b112","doi-asserted-by":"crossref","first-page":"1698","DOI":"10.1109\/TPAMI.2005.209","article-title":"A biometric identification system based on eigenpalm and eigenfinger features","volume":"27","author":"Ribaric","year":"2005","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2022.10.032_b113","series-title":"18th International Conference on Pattern Recognition (ICPR\u201906)","first-page":"549","article-title":"Combining fingerprint, palmprint and hand-shape for user authentication","volume":"4","author":"Kumar","year":"2006"},{"key":"10.1016\/j.inffus.2022.10.032_b114","series-title":"Fourth Annual ACIS International Conference on Computer and Information Science (ICIS\u201905)","first-page":"94","article-title":"Palmprint identification algorithm using hu invariant moments and otsu binarization","author":"Noh","year":"2005"},{"issue":"2","key":"10.1016\/j.inffus.2022.10.032_b115","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1109\/TCSVT.2003.821978","article-title":"On hierarchical palmprint coding with multiple features for personal identification in large databases","volume":"14","author":"You","year":"2004","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.inffus.2022.10.032_b116","series-title":"Proceedings. International Conference on Machine Learning and Cybernetics","first-page":"1253","article-title":"Wavelet based palm print recognition","volume":"3","author":"Wu","year":"2002"},{"key":"10.1016\/j.inffus.2022.10.032_b117","series-title":"Third International Conference on Image and Graphics (ICIG\u201904)","first-page":"258","article-title":"Palmprint identification using palmcodes","author":"Kumar","year":"2004"},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b118","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1109\/89.365379","article-title":"Robust text-independent speaker identification using Gaussian mixture speaker models","volume":"3","author":"Reynolds","year":"1995","journal-title":"IEEE Trans. Speech Audio Process."},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b119","first-page":"11","article-title":"Improved text-independent speaker identification using fused MFCC & IMFCC feature sets based on Gaussian filter","volume":"5","author":"Chakroborty","year":"2009","journal-title":"Int. J. Signal Process."},{"issue":"4","key":"10.1016\/j.inffus.2022.10.032_b120","doi-asserted-by":"crossref","first-page":"836","DOI":"10.1109\/TASLP.2014.2308398","article-title":"Robust speaker identification in noisy and reverberant conditions","volume":"22","author":"Zhao","year":"2014","journal-title":"IEEE\/ACM Trans. Audio. Speech. Lang. Process."},{"issue":"44","key":"10.1016\/j.inffus.2022.10.032_b121","doi-asserted-by":"crossref","DOI":"10.17485\/ijst\/2016\/v9i44\/90003","article-title":"Speaker identification using a novel prosody with fuzzy based hierarchical decision tree approach","volume":"9","author":"Manikandan","year":"2016","journal-title":"Indian J. Sci. Technol."},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b122","doi-asserted-by":"crossref","first-page":"504","DOI":"10.3390\/make1010031","article-title":"A near real-time automatic speaker recognition architecture for voice-based user interface","volume":"1","author":"Dhakal","year":"2019","journal-title":"Mach. Learn. Knowl. Extr."},{"issue":"4 (Special Issue)","key":"10.1016\/j.inffus.2022.10.032_b123","first-page":"566","article-title":"Kurdish speaker identification based on one dimensional convolutional neural network","volume":"7","author":"Abdul","year":"2019","journal-title":"Comput. Methods Differ. Equ."},{"key":"10.1016\/j.inffus.2022.10.032_b124","series-title":"2015 International Conference on Computers, Communications, and Systems","first-page":"223","article-title":"Speaker identification using bagging techniques","author":"Indumathi","year":"2015"},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b125","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13636-015-0056-7","article-title":"Deep neural network-based bottleneck feature and denoising autoencoder-based dereverberation for distant-talking speaker identification","volume":"2015","author":"Zhang","year":"2015","journal-title":"EURASIP J. Audio Speech Music Process."},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b126","doi-asserted-by":"crossref","first-page":"574","DOI":"10.15181\/csat.v6i1.1579","article-title":"Building LSTM neural network based speaker identification system","volume":"6","author":"Dovydaitis","year":"2018","journal-title":"Comput. Sci. Techn."},{"issue":"9","key":"10.1016\/j.inffus.2022.10.032_b127","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1109\/TASLP.2018.2831456","article-title":"Text-independent speaker verification based on triplet convolutional neural network embeddings","volume":"26","author":"Zhang","year":"2018","journal-title":"IEEE\/ACM Trans. Audio Speech Language Process."},{"issue":"6","key":"10.1016\/j.inffus.2022.10.032_b128","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1109\/TPAMI.2004.18","article-title":"Automatic writer identification using connected-component contours and edge-based features of uppercase western script","volume":"26","author":"Schomaker","year":"2004","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2022.10.032_b129","series-title":"2016 23rd International Conference on Pattern Recognition","first-page":"3025","article-title":"Multi-script writer identification using dissimilarity","author":"Bertolini","year":"2016"},{"key":"10.1016\/j.inffus.2022.10.032_b130","doi-asserted-by":"crossref","unstructured":"A. Seropian, M. Grimaldi, N. Vincent, Writer Identification based on the fractal construction of a reference base, in: ICDAR, 2003, pp. 1163\u20131167.","DOI":"10.1109\/ICDAR.2003.1227840"},{"key":"10.1016\/j.inffus.2022.10.032_b131","series-title":"2008 19th International Conference on Pattern Recognition","first-page":"1","article-title":"How much handwritten text is needed for text-independent writer verification and identification","author":"Brink","year":"2008"},{"issue":"4","key":"10.1016\/j.inffus.2022.10.032_b132","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1109\/TPAMI.2007.1009","article-title":"Text-independent writer identification and verification using textural and allographic features","volume":"29","author":"Bulacu","year":"2007","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2022.10.032_b133","series-title":"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings","first-page":"413","article-title":"Writer identification using innovative binarised features of handwritten numerals","author":"Leedham","year":"2003"},{"issue":"3","key":"10.1016\/j.inffus.2022.10.032_b134","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1016\/j.patcog.2006.08.008","article-title":"Extraction and analysis of forensic document examiner features used for writer identification","volume":"40","author":"Pervouchine","year":"2007","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.inffus.2022.10.032_b135","series-title":"International Conference on Computer Analysis of Images and Patterns","first-page":"26","article-title":"Writer identification and retrieval using a convolutional neural network","author":"Fiel","year":"2015"},{"key":"10.1016\/j.inffus.2022.10.032_b136","series-title":"2016 15th International Conference on Frontiers in Handwriting Recognition","first-page":"584","article-title":"Deepwriter: A multi-stream deep CNN for text-independent writer identification","author":"Xing","year":"2016"},{"key":"10.1016\/j.inffus.2022.10.032_b137","doi-asserted-by":"crossref","unstructured":"R. Nasuno, S. Arai, Writer identification for offline japanese handwritten character using convolutional neural network, in: Proceedings of the 5th IIAE (Institute of Industrial Applications Engineers) International Conference on Intelligent Systems and Image Processing, 2017, pp. 94\u201397.","DOI":"10.12792\/icisip2017.020"},{"key":"10.1016\/j.inffus.2022.10.032_b138","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1016\/j.patcog.2016.10.005","article-title":"Writer identification using GMM supervectors and exemplar-SVMs","volume":"63","author":"Christlein","year":"2017","journal-title":"Pattern Recognit."},{"issue":"2","key":"10.1016\/j.inffus.2022.10.032_b139","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1109\/THMS.2016.2634921","article-title":"End-to-end online writer identification with recurrent neural network","volume":"47","author":"Zhang","year":"2016","journal-title":"IEEE Trans. Hum.-Mach. Syst."},{"key":"10.1016\/j.inffus.2022.10.032_b140","series-title":"2016 International Conference on Progress in Informatics and Computing","first-page":"432","article-title":"An offline text-independent writer identification system with sae feature extraction","author":"Zhu","year":"2016"},{"issue":"2","key":"10.1016\/j.inffus.2022.10.032_b141","doi-asserted-by":"crossref","first-page":"259","DOI":"10.4218\/etrij.11.1510.0068","article-title":"Automated markerless analysis of human gait motion for recognition and classification","volume":"33","author":"Yoo","year":"2011","journal-title":"Etri J."},{"issue":"6","key":"10.1016\/j.inffus.2022.10.032_b142","doi-asserted-by":"crossref","first-page":"754","DOI":"10.1016\/j.jvlc.2014.10.004","article-title":"Gait recognition based on joint distribution of motion angles","volume":"25","author":"Lu","year":"2014","journal-title":"J. Vis. Lang. Comput."},{"issue":"3","key":"10.1016\/j.inffus.2022.10.032_b143","doi-asserted-by":"crossref","first-page":"780","DOI":"10.1016\/j.sigpro.2011.09.022","article-title":"Gait recognition using pose kinematics and pose energy image","volume":"92","author":"Roy","year":"2012","journal-title":"Signal Process."},{"issue":"4","key":"10.1016\/j.inffus.2022.10.032_b144","doi-asserted-by":"crossref","DOI":"10.1117\/1.JEI.22.4.043039","article-title":"Gait recognition based on gabor wavelets and modified gait energy image for human identification","volume":"22","author":"Huang","year":"2013","journal-title":"J. Electron. Imaging"},{"key":"10.1016\/j.inffus.2022.10.032_b145","series-title":"2009 International Conference on Machine Learning and Cybernetics","first-page":"50","article-title":"Gait recognition using dynamic gait energy and PCA+ LPP method","volume":"1","author":"Zhang","year":"2009"},{"key":"10.1016\/j.inffus.2022.10.032_b146","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.jvcir.2015.09.006","article-title":"Gait recognition with transient binary patterns","volume":"33","author":"Lee","year":"2015","journal-title":"J. Vis. Commun. Image Represent."},{"issue":"9","key":"10.1016\/j.inffus.2022.10.032_b147","doi-asserted-by":"crossref","first-page":"3414","DOI":"10.1016\/j.patcog.2012.02.032","article-title":"Silhouette-based gait recognition using procrustes shape analysis and elliptic Fourier descriptors","volume":"45","author":"Choudhury","year":"2012","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.inffus.2022.10.032_b148","series-title":"6th International Conference on Mobile Computing, Applications and Services","first-page":"197","article-title":"Convolutional neural networks for human activity recognition using mobile sensors","author":"Zeng","year":"2014"},{"issue":"2","key":"10.1016\/j.inffus.2022.10.032_b149","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1109\/TPAMI.2016.2545669","article-title":"A comprehensive study on cross-view gait based human identification with deep cnns","volume":"39","author":"Wu","year":"2016","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"9","key":"10.1016\/j.inffus.2022.10.032_b150","doi-asserted-by":"crossref","first-page":"2708","DOI":"10.1109\/TCSVT.2017.2760835","article-title":"On input\/output architectures for convolutional neural network-based cross-view gait recognition","volume":"29","author":"Takemura","year":"2017","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b151","doi-asserted-by":"crossref","first-page":"115","DOI":"10.3390\/s16010115","article-title":"Deep convolutional and lstm recurrent neural networks for multimodal wearable activity recognition","volume":"16","author":"Ord\u00f3\u00f1ez","year":"2016","journal-title":"Sensors"},{"key":"10.1016\/j.inffus.2022.10.032_b152","series-title":"Convolutional lstm networks for video-based person re-identification","author":"Wu","year":"2016"},{"key":"10.1016\/j.inffus.2022.10.032_b153","doi-asserted-by":"crossref","unstructured":"S. Yu, H. Chen, E.B. Garcia\u00a0Reyes, N. Poh, Gaitgan: Invariant gait feature extraction using generative adversarial networks, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017, pp. 30\u201337.","DOI":"10.1109\/CVPRW.2017.80"},{"issue":"3","key":"10.1016\/j.inffus.2022.10.032_b154","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1109\/CJECE.2004.1532524","article-title":"An experimental performance evaluation of a novel radio-transmitter identification system under diverse environmental conditions","volume":"29","author":"Tekbas","year":"2004","journal-title":"Can. J. Electr. Comput. Eng."},{"issue":"6","key":"10.1016\/j.inffus.2022.10.032_b155","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1049\/el:20057769","article-title":"Bayesian detection of wi-fi transmitter RF fingerprints","volume":"41","author":"Ureten","year":"2005","journal-title":"Electron. Lett."},{"key":"10.1016\/j.inffus.2022.10.032_b156","series-title":"2007 Third International Conference on Security and Privacy in Communications Networks and the Workshops-SecureComm 2007","first-page":"331","article-title":"Implications of radio fingerprinting on the security of sensor networks","author":"Rasmussen","year":"2007"},{"key":"10.1016\/j.inffus.2022.10.032_b157","series-title":"MILCOM 2008-2008 IEEE Military Communications Conference","first-page":"1","article-title":"Individual radio transmitter identification based on spurious modulation characteristics of signal envelop","author":"Xu","year":"2008"},{"key":"10.1016\/j.inffus.2022.10.032_b158","doi-asserted-by":"crossref","unstructured":"V. Brik, S. Banerjee, M. Gruteser, S. Oh, Wireless device identification with radiometric signatures, in: Proceedings of the 14th ACM International Conference on Mobile Computing and Networking, 2008, pp. 116\u2013127.","DOI":"10.1145\/1409944.1409959"},{"key":"10.1016\/j.inffus.2022.10.032_b159","series-title":"IEEE GLOBECOM 2008-2008 IEEE Global Telecommunications Conference","first-page":"1","article-title":"Using spectral fingerprints to improve wireless network security","author":"Suski\u00a0II","year":"2008"},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b160","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1109\/JIOT.2016.2619679","article-title":"S2M: A lightweight acoustic fingerprints-based wireless device authentication protocol","volume":"4","author":"Chen","year":"2016","journal-title":"IEEE Internet Things J."},{"key":"10.1016\/j.inffus.2022.10.032_b161","series-title":"2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking","first-page":"1","article-title":"Wiau: An accurate device-free authentication system with ResNet","author":"Lin","year":"2018"},{"key":"10.1016\/j.inffus.2022.10.032_b162","series-title":"2018 IEEE International Conference on Internet of Things and Intelligence System","first-page":"174","article-title":"IoT device fingerprint using deep learning","author":"Aneja","year":"2018"},{"key":"10.1016\/j.inffus.2022.10.032_b163","article-title":"Imagenet classification with deep convolutional neural networks","volume":"25","author":"Krizhevsky","year":"2012","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"6","key":"10.1016\/j.inffus.2022.10.032_b164","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1109\/MSP.2012.2205597","article-title":"Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups","volume":"29","author":"Hinton","year":"2012","journal-title":"IEEE Signal Process. Mag."},{"key":"10.1016\/j.inffus.2022.10.032_b165","series-title":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing","first-page":"5200","article-title":"Adieu features? end-to-end speech emotion recognition using a deep convolutional recurrent network","author":"Trigeorgis","year":"2016"},{"issue":"11","key":"10.1016\/j.inffus.2022.10.032_b166","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1109\/35.41402","article-title":"Integration of acoustic and visual speech signals using neural networks","volume":"27","author":"Yuhas","year":"1989","journal-title":"IEEE Commun. Mag."},{"key":"10.1016\/j.inffus.2022.10.032_b167","series-title":"7th Iberian Conference on Information Systems and Technologies (CISTI 2012)","first-page":"1","article-title":"Comparison between decision-level and feature-level fusion of acoustic and linguistic features for spontaneous emotion recognition","author":"Planet","year":"2012"},{"key":"10.1016\/j.inffus.2022.10.032_b168","series-title":"2013 International Conference on Signal-Image Technology & Internet-Based Systems","first-page":"706","article-title":"Feature level fusion of face and signature using a modified feature selection technique","author":"Awang","year":"2013"},{"key":"10.1016\/j.inffus.2022.10.032_b169","series-title":"2018 Ieee International Conference on System, Computation, Automation and Networking (Icscan)","first-page":"1","article-title":"A framework for level-1 and level-2 feature level fusion","author":"Poonguzhali","year":"2018"},{"issue":"12","key":"10.1016\/j.inffus.2022.10.032_b170","doi-asserted-by":"crossref","first-page":"16345","DOI":"10.1007\/s11042-018-7012-3","article-title":"Multimodal biometric scheme for human authentication technique based on voice and face recognition fusion","volume":"78","author":"Abozaid","year":"2019","journal-title":"Multimedia Tools Appl."},{"key":"10.1016\/j.inffus.2022.10.032_b171","series-title":"ICC 2019-2019 IEEE International Conference on Communications","first-page":"1","article-title":"Multi-modal face authentication using deep visual and acoustic features","author":"Zhou","year":"2019"},{"key":"10.1016\/j.inffus.2022.10.032_b172","first-page":"1","article-title":"Ann trained and WOA optimized feature-level fusion of iris and fingerprint","volume":"51","author":"Kumar","year":"2022","journal-title":"Mater. Today: Proceedings"},{"key":"10.1016\/j.inffus.2022.10.032_b173","doi-asserted-by":"crossref","DOI":"10.1111\/exsy.12523","article-title":"Selection of optimized features for fusion of palm print and finger knuckle-based person authentication","volume":"38","author":"Jaswal","year":"2021","journal-title":"Expert Syst."},{"issue":"4","key":"10.1016\/j.inffus.2022.10.032_b174","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1007\/s11760-020-01806-0","article-title":"Feature-level fusion of major and minor dorsal finger knuckle patterns for person authentication","volume":"15","author":"Attia","year":"2021","journal-title":"Signal, Image Video Process."},{"key":"10.1016\/j.inffus.2022.10.032_b175","series-title":"2019 10th International Conference on Computing, Communication and Networking Technologies","first-page":"1","article-title":"Secure multimodal biometric authentication using face, palmprint and ear: a feature level fusion approach","author":"Bokade","year":"2019"},{"issue":"4","key":"10.1016\/j.inffus.2022.10.032_b176","doi-asserted-by":"crossref","first-page":"1790","DOI":"10.1109\/TCE.2008.4711236","article-title":"Multimodal biometric authentication using teeth image and voice in mobile environment","volume":"54","author":"Kim","year":"2008","journal-title":"IEEE Trans. Consum. Electron."},{"key":"10.1016\/j.inffus.2022.10.032_b177","series-title":"2014 Seventh International Symposium on Computational Intelligence and Design","first-page":"441","article-title":"Palm vein recognition based on multi-algorithm and score-level fusion","volume":"1","author":"Yan","year":"2014"},{"issue":"2","key":"10.1016\/j.inffus.2022.10.032_b178","article-title":"Multimodal score-level fusion using hybrid ga-pso for multibiometric system","volume":"39","author":"Dalila","year":"2015","journal-title":"Informatica"},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b179","doi-asserted-by":"crossref","first-page":"1498","DOI":"10.1016\/j.jksuci.2019.09.003","article-title":"Score level fusion in multi-biometric identification based on zones of interest","volume":"34","author":"Aizi","year":"2022","journal-title":"J. King Saud University-Comput. Inf. Sci."},{"issue":"6","key":"10.1016\/j.inffus.2022.10.032_b180","doi-asserted-by":"crossref","first-page":"1193","DOI":"10.1109\/TIFS.2015.2402593","article-title":"A new biocryptosystem-oriented security analysis framework and implementation of multibiometric cryptosystems based on decision level fusion","volume":"10","author":"Li","year":"2015","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"10.1016\/j.inffus.2022.10.032_b181","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.neucom.2016.01.006","article-title":"Joint encryption and compression scheme for a multimodal telebiometric system","volume":"191","author":"Naik","year":"2016","journal-title":"Neurocomputing"},{"key":"10.1016\/j.inffus.2022.10.032_b182","series-title":"2020 IEEE International Conference on Electronics, Computing and Communication Technologies","first-page":"1","article-title":"Decision level fusion schemes for a multimodal biometric system using local and global wavelet features","author":"Devi","year":"2020"},{"key":"10.1016\/j.inffus.2022.10.032_b183","series-title":"Security and Privacy","first-page":"1","article-title":"A score-level fusion method for protecting fingerprint and palmprint templates","author":"Sandhya","year":"2021"},{"issue":"5","key":"10.1016\/j.inffus.2022.10.032_b184","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1109\/TSMCC.2010.2089516","article-title":"Personal identification using multibiometrics rank-level fusion","volume":"41","author":"Kumar","year":"2010","journal-title":"IEEE Trans. Syst. Man Cybern. C"},{"key":"10.1016\/j.inffus.2022.10.032_b185","series-title":"2011 International Conference on Intelligent Computation and Bio-Medical Instrumentation","first-page":"208","article-title":"A novel rank-level fusion for multispectral palmprint identification system","author":"Tahmasebi","year":"2011"},{"key":"10.1016\/j.inffus.2022.10.032_b186","series-title":"2017 IEEE Symposium Series on Computational Intelligence","first-page":"1","article-title":"Rank level fusion for kinect gait and face biometrie identification","author":"Rahman","year":"2017"},{"issue":"7","key":"10.1016\/j.inffus.2022.10.032_b187","first-page":"969","article-title":"Finger surfaces recognition using rank level fusion","volume":"60","author":"Ben\u00a0Jemaa","year":"2017","journal-title":"Comput. J."},{"key":"10.1016\/j.inffus.2022.10.032_b188","doi-asserted-by":"crossref","first-page":"157663","DOI":"10.1109\/ACCESS.2020.3018958","article-title":"Score and rank level fusion algorithms for social behavioral biometrics","volume":"8","author":"Tumpa","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.inffus.2022.10.032_b189","first-page":"1","article-title":"Comparative analysis of distinct fusion levels in multimodal biometrics","volume":"4","author":"Kumar","year":"2015","journal-title":"Int. J. Comput. Appl."},{"key":"10.1016\/j.inffus.2022.10.032_b190","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.inffus.2018.07.005","article-title":"Confidence factor weighted Gaussian function induced parallel fuzzy rank-level fusion for inference and its application to face recognition","volume":"47","author":"Sing","year":"2019","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.inffus.2022.10.032_b191","series-title":"2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics","first-page":"1","article-title":"Rank level fusion in multibiometric systems","author":"Sharma","year":"2015"},{"key":"10.1016\/j.inffus.2022.10.032_b192","series-title":"2016 IEEE International Conference on Computational Intelligence and Computing Research","first-page":"1","article-title":"A multimodal biometric system using partition based dwt and rank level fusion","author":"Devi","year":"2016"},{"key":"10.1016\/j.inffus.2022.10.032_b193","series-title":"2009 International Conference on Advances in Recent Technologies in Communication and Computing","first-page":"596","article-title":"A multimodal biometric recognition system based on fusion of palmprint, fingerprint and face","author":"Chaudhary","year":"2009"},{"issue":"2","key":"10.1016\/j.inffus.2022.10.032_b194","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1109\/TPAMI.2018.2798607","article-title":"Multimodal machine learning: A survey and taxonomy","volume":"41","author":"Baltru\u0161aitis","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"5786","key":"10.1016\/j.inffus.2022.10.032_b195","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1126\/science.1127647","article-title":"Reducing the dimensionality of data with neural networks","volume":"313","author":"Hinton","year":"2006","journal-title":"Science"},{"key":"10.1016\/j.inffus.2022.10.032_b196","doi-asserted-by":"crossref","unstructured":"H.P. Mart\u00ednez, G.N. Yannakakis, Deep multimodal fusion: Combining discrete events and continuous signals, in: Proceedings of the 16th International Conference on Multimodal Interaction, 2014, pp. 34\u201341.","DOI":"10.1145\/2663204.2663236"},{"key":"10.1016\/j.inffus.2022.10.032_b197","series-title":"2007 International Conference on Wavelet Analysis and Pattern Recognition","first-page":"1203","article-title":"Multimodal recognition based on face and ear","volume":"3","author":"Yuan","year":"2007"},{"issue":"4","key":"10.1016\/j.inffus.2022.10.032_b198","doi-asserted-by":"crossref","first-page":"867","DOI":"10.1109\/TSMCB.2008.2009071","article-title":"Multimodal biometric system using rank-level fusion approach","volume":"39","author":"Monwar","year":"2009","journal-title":"IEEE Trans. Syst. Man Cybern. B"},{"key":"10.1016\/j.inffus.2022.10.032_b199","series-title":"ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005","first-page":"12","article-title":"A biometric verification system based on the fusion of palmprint and face features","author":"Ribaric","year":"2005"},{"key":"10.1016\/j.inffus.2022.10.032_b200","series-title":"IEEE-International Conference on Advances in Engineering, Science and Management (ICAESM-2012)","first-page":"174","article-title":"Multimodal biometric recognition using iris feature extraction and palmprint features","author":"Hariprasath","year":"2012"},{"key":"10.1016\/j.inffus.2022.10.032_b201","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.patrec.2015.09.009","article-title":"Multimodal authentication on smartphones: Combining iris and sensor recognition for a double check of user identity","volume":"82","author":"Galdi","year":"2016","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.inffus.2022.10.032_b202","series-title":"International Conference on Biometrics","first-page":"744","article-title":"Feature-level fusion of hand biometrics for personal verification based on kernel PCA","author":"Li","year":"2006"},{"key":"10.1016\/j.inffus.2022.10.032_b203","series-title":"2011 IEEE International Conference on Communications","first-page":"1","article-title":"Fusion of finger-knuckle-print and palmprint for an efficient multi-biometric system of person recognition","author":"Meraoumia","year":"2011"},{"issue":"8","key":"10.1016\/j.inffus.2022.10.032_b204","doi-asserted-by":"crossref","first-page":"10961","DOI":"10.1007\/s11042-022-12384-3","article-title":"Deep learning-driven palmprint and finger knuckle pattern-based multimodal person recognition system","volume":"81","author":"Attia","year":"2022","journal-title":"Multimedia Tools Appl."},{"key":"10.1016\/j.inffus.2022.10.032_b205","series-title":"International Conference on Information Systems, Technology and Management","first-page":"363","article-title":"Fusion of speech and face by enhanced modular neural network","author":"Kala","year":"2010"},{"key":"10.1016\/j.inffus.2022.10.032_b206","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"3581","article-title":"Look, listen and learn\u2014A multimodal LSTM for speaker identification","author":"Ren","year":"2016"},{"key":"10.1016\/j.inffus.2022.10.032_b207","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1016\/j.patcog.2018.12.011","article-title":"Attention guided deep audio-face fusion for efficient speaker naming","volume":"88","author":"Liu","year":"2019","journal-title":"Pattern Recognit."},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b208","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1109\/TASLP.2017.2760243","article-title":"Robust voice liveness detection and speaker verification using throat microphones","volume":"26","author":"Sahidullah","year":"2017","journal-title":"IEEE\/ACM Trans. Audio Speech Lang. Process."},{"key":"10.1016\/j.inffus.2022.10.032_b209","doi-asserted-by":"crossref","first-page":"1572","DOI":"10.1109\/TIFS.2019.2944058","article-title":"LVID: A multimodal biometrics authentication system on smartphones","volume":"15","author":"Wu","year":"2019","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"issue":"2","key":"10.1016\/j.inffus.2022.10.032_b210","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1109\/2.820041","article-title":"BiolD: a multimodal biometric identification system","volume":"33","author":"Frischholz","year":"2000","journal-title":"Computer"},{"key":"10.1016\/j.inffus.2022.10.032_b211","series-title":"INTERSPEECH","first-page":"2247","article-title":"Multimodal association for speaker verification","author":"Shon","year":"2020"},{"key":"10.1016\/j.inffus.2022.10.032_b212","doi-asserted-by":"crossref","unstructured":"S. Nawaz, M.S. Saeed, P. Morerio, A. Mahmood, I. Gallo, M.H. Yousaf, A. Del\u00a0Bue, Cross-modal Speaker Verification and Recognition: A Multilingual Perspective, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 1682\u20131691.","DOI":"10.1109\/CVPRW53098.2021.00184"},{"issue":"5","key":"10.1016\/j.inffus.2022.10.032_b213","doi-asserted-by":"crossref","first-page":"3500","DOI":"10.1109\/JIOT.2020.3023101","article-title":"Secure mmwave-radar-based speaker verification for IoT smart home","volume":"8","author":"Dong","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"10.1016\/j.inffus.2022.10.032_b214","doi-asserted-by":"crossref","first-page":"94625","DOI":"10.1109\/ACCESS.2021.3092840","article-title":"Multimodal EEG and keystroke dynamics based biometric system using machine learning algorithms","volume":"9","author":"Rahman","year":"2021","journal-title":"IEEE Access"},{"key":"10.1016\/j.inffus.2022.10.032_b215","series-title":"2019 IEEE 9th Symposium on Computer Applications & Industrial Electronics","first-page":"125","article-title":"Behavioral biometrics scheme with keystroke and swipe dynamics for user authentication on mobile platform","author":"Tse","year":"2019"},{"issue":"12","key":"10.1016\/j.inffus.2022.10.032_b216","doi-asserted-by":"crossref","first-page":"3116","DOI":"10.1109\/TIFS.2019.2911170","article-title":"Multi-modal biometric-based implicit authentication of wearable device users","volume":"14","author":"Vhaduri","year":"2019","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"10.1016\/j.inffus.2022.10.032_b217","series-title":"2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications","first-page":"1","article-title":"Context-dependent implicit authentication for wearable device users","author":"Cheung","year":"2020"},{"key":"10.1016\/j.inffus.2022.10.032_b218","series-title":"2019 32nd International Conference on VLSI Design and 2019 18th International Conference on Embedded Systems","first-page":"539","article-title":"Continuous transparent mobile device touchscreen soft keyboard biometric authentication","author":"Dee","year":"2019"},{"key":"10.1016\/j.inffus.2022.10.032_b219","series-title":"2019 IEEE International Conference on Power Data Science","first-page":"126","article-title":"G-key: An authentication technique for mobile devices based on gravity sensors","author":"Xie","year":"2019"},{"issue":"3","key":"10.1016\/j.inffus.2022.10.032_b220","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1109\/TFUZZ.2019.2956896","article-title":"A fuzzy authentication system based on neural network learning and extreme value statistics","volume":"29","author":"Qin","year":"2019","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"10.1016\/j.inffus.2022.10.032_b221","series-title":"2019 European Intelligence and Security Informatics Conference","first-page":"140","article-title":"Mobile user authentication using keystroke dynamics","author":"Frolova","year":"2019"},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b222","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1109\/TCE.2021.3055419","article-title":"A robust biometric authentication system for handheld electronic devices by intelligently combining 3D finger motions and cerebral responses","volume":"67","author":"Behera","year":"2021","journal-title":"IEEE Trans. Consum. Electron."},{"key":"10.1016\/j.inffus.2022.10.032_b223","article-title":"Enabling finger-touch-based mobile user authentication via physical vibrations on IoT devices","author":"Yang","year":"2021","journal-title":"IEEE Trans. Mob. Comput."},{"key":"10.1016\/j.inffus.2022.10.032_b224","series-title":"2019 International Conference on Computing, Networking and Communications","first-page":"425","article-title":"Privacy-preserving device discovery and authentication scheme for D2D communication in 3GPP 5G HetNet","author":"Sun","year":"2019"},{"key":"10.1016\/j.inffus.2022.10.032_b225","series-title":"2020 International Conference on Power Electronics & IoT Applications in Renewable Energy and Its Control","first-page":"539","article-title":"Multiple degree authentication in sensible homes basedon iot device vulnerability","author":"Sharma","year":"2020"},{"issue":"1","key":"10.1016\/j.inffus.2022.10.032_b226","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1109\/JIOT.2018.2846299","article-title":"Lightweight and privacy-preserving two-factor authentication scheme for IoT devices","volume":"6","author":"Gope","year":"2018","journal-title":"IEEE Internet Things J."},{"key":"10.1016\/j.inffus.2022.10.032_b227","series-title":"2020 IEEE Wireless Communications and Networking Conference","first-page":"1","article-title":"Wearable proxy device-assisted authentication request filtering for implantable medical devices","author":"Zhang","year":"2020"},{"key":"10.1016\/j.inffus.2022.10.032_b228","series-title":"Intriguing properties of neural networks","author":"Szegedy","year":"2013"},{"key":"10.1016\/j.inffus.2022.10.032_b229","doi-asserted-by":"crossref","unstructured":"N. Akhtar, J. Liu, A. Mian, Defense against universal adversarial perturbations, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 3389\u20133398.","DOI":"10.1109\/CVPR.2018.00357"},{"key":"10.1016\/j.inffus.2022.10.032_b230","doi-asserted-by":"crossref","unstructured":"A. Nguyen, J. Yosinski, J. Clune, Deep neural networks are easily fooled: High confidence predictions for unrecognizable images, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 427\u2013436.","DOI":"10.1109\/CVPR.2015.7298640"},{"key":"10.1016\/j.inffus.2022.10.032_b231","series-title":"Detecting adversarial samples from artifacts","author":"Feinman","year":"2017"},{"key":"10.1016\/j.inffus.2022.10.032_b232","doi-asserted-by":"crossref","first-page":"14410","DOI":"10.1109\/ACCESS.2018.2807385","article-title":"Threat of adversarial attacks on deep learning in computer vision: A survey","volume":"6","author":"Akhtar","year":"2018","journal-title":"Ieee Access"},{"key":"10.1016\/j.inffus.2022.10.032_b233","series-title":"Adversarial manipulation of deep representations","author":"Sabour","year":"2015"},{"key":"10.1016\/j.inffus.2022.10.032_b234","series-title":"Explaining and harnessing adversarial examples","author":"Goodfellow","year":"2014"},{"key":"10.1016\/j.inffus.2022.10.032_b235","series-title":"2021 IEEE International Intelligent Transportation Systems Conference","first-page":"3652","article-title":"Black-box adversarial attacks on network-wide multi-step traffic state prediction models","author":"Poudel","year":"2021"},{"key":"10.1016\/j.inffus.2022.10.032_b236","series-title":"Towards deep learning models resistant to adversarial attacks","author":"Madry","year":"2017"},{"key":"10.1016\/j.inffus.2022.10.032_b237","series-title":"International Conference on Machine Learning","first-page":"2206","article-title":"Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks","author":"Croce","year":"2020"},{"key":"10.1016\/j.inffus.2022.10.032_b238","doi-asserted-by":"crossref","unstructured":"S.-M. Moosavi-Dezfooli, A. Fawzi, P. Frossard, Deepfool: a simple and accurate method to fool deep neural networks, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 2574\u20132582.","DOI":"10.1109\/CVPR.2016.282"},{"key":"10.1016\/j.inffus.2022.10.032_b239","doi-asserted-by":"crossref","unstructured":"S.-M. Moosavi-Dezfooli, A. Fawzi, O. Fawzi, P. Frossard, Universal adversarial perturbations, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 1765\u20131773.","DOI":"10.1109\/CVPR.2017.17"},{"issue":"5","key":"10.1016\/j.inffus.2022.10.032_b240","doi-asserted-by":"crossref","first-page":"828","DOI":"10.1109\/TEVC.2019.2890858","article-title":"One pixel attack for fooling deep neural networks","volume":"23","author":"Su","year":"2019","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.inffus.2022.10.032_b241","doi-asserted-by":"crossref","first-page":"1038","DOI":"10.1109\/TIFS.2022.3156809","article-title":"Decision-based adversarial attack with frequency mixup","volume":"17","author":"Li","year":"2022","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"10.1016\/j.inffus.2022.10.032_b242","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2021.108306","article-title":"A black-box adversarial attack for poisoning clustering","volume":"122","author":"Cin\u00e0","year":"2022","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.inffus.2022.10.032_b243","doi-asserted-by":"crossref","DOI":"10.1109\/TPAMI.2020.3033291","article-title":"Universal adversarial attack on attention and the resulting dataset damagenet","author":"Chen","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.inffus.2022.10.032_b244","series-title":"2017 Ieee Symposium on Security and Privacy (Sp)","first-page":"39","article-title":"Towards evaluating the robustness of neural networks","author":"Carlini","year":"2017"},{"key":"10.1016\/j.inffus.2022.10.032_b245","series-title":"2019 International Joint Conference on Neural Networks","first-page":"1","article-title":"A comprehensive analysis on adversarial robustness of spiking neural networks","author":"Sharmin","year":"2019"},{"key":"10.1016\/j.inffus.2022.10.032_b246","series-title":"2016 IEEE Symposium on Security and Privacy","first-page":"582","article-title":"Distillation as a defense to adversarial perturbations against deep neural networks","author":"Papernot","year":"2016"},{"key":"10.1016\/j.inffus.2022.10.032_b247","article-title":"Using self-supervised learning can improve model robustness and uncertainty","volume":"32","author":"Hendrycks","year":"2019","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.inffus.2022.10.032_b248","series-title":"2019 IEEE European Symposium on Security and Privacy (EuroS&P)","first-page":"512","article-title":"PRADA: protecting against DNN model stealing attacks","author":"Juuti","year":"2019"},{"issue":"4","key":"10.1016\/j.inffus.2022.10.032_b249","doi-asserted-by":"crossref","first-page":"1070","DOI":"10.1007\/s11263-022-01581-0","article-title":"Open-set adversarial defense with clean-adversarial mutual learning","volume":"130","author":"Shao","year":"2022","journal-title":"Int. J. Comput. Vis."},{"issue":"3","key":"10.1016\/j.inffus.2022.10.032_b250","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1109\/TCSS.2020.3042628","article-title":"Smoothing adversarial training for gnn","volume":"8","author":"Chen","year":"2020","journal-title":"IEEE Trans. Comput. Soc. Syst."},{"key":"10.1016\/j.inffus.2022.10.032_b251","doi-asserted-by":"crossref","first-page":"22617","DOI":"10.1109\/ACCESS.2020.2969288","article-title":"Adversarial dual network learning with randomized image transform for restoring attacked images","volume":"8","author":"Yuan","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.inffus.2022.10.032_b252","series-title":"ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing","first-page":"3277","article-title":"Efficient randomized defense against adversarial attacks in deep convolutional neural networks","author":"Sheikholeslami","year":"2019"},{"key":"10.1016\/j.inffus.2022.10.032_b253","series-title":"2018 IEEE European Symposium on Security and Privacy (EuroS&P)","first-page":"488","article-title":"Forgotten siblings: Unifying attacks on machine learning and digital watermarking","author":"Quiring","year":"2018"},{"key":"10.1016\/j.inffus.2022.10.032_b254","unstructured":"Y. Wang, D. Zou, J. Yi, J. Bailey, X. Ma, Q. Gu, Improving adversarial robustness requires revisiting misclassified examples, in: International Conference on Learning Representations, 2019."}],"container-title":["Information Fusion"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1566253522002081?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1566253522002081?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T13:22:13Z","timestamp":1761571333000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1566253522002081"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3]]},"references-count":254,"alternative-id":["S1566253522002081"],"URL":"https:\/\/doi.org\/10.1016\/j.inffus.2022.10.032","relation":{},"ISSN":["1566-2535"],"issn-type":[{"value":"1566-2535","type":"print"}],"subject":[],"published":{"date-parts":[[2023,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A survey of identity recognition via data fusion and feature learning","name":"articletitle","label":"Article Title"},{"value":"Information Fusion","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.inffus.2022.10.032","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2022 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}]}}