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Deepak Ranjan Nayak
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2020 – today
- 2024
- [j35]Tapas Kumar Dutta, Deepak Ranjan Nayak
, Yu-Dong Zhang
ARM-Net: Attention-guided residual multiscale CNN for multiclass brain tumor classification using MR images. Biomed. Signal Process. Control. 87(Part A): 105421 (2024) - [j34]Dipankar Das, Deepak Ranjan Nayak
CDAM-Net: Channel shuffle dual attention based multi-scale CNN for efficient glaucoma detection using fundus images. Eng. Appl. Artif. Intell. 133: 108454 (2024) - [j33]Babita
RDTNet: A residual deformable attention based transformer network for breast cancer classification. Expert Syst. Appl. 249: 123569 (2024) - [j32]Dipankar Das, Deepak Ranjan Nayak, Ram Bilas Pachori:
AES-Net: An adapter and enhanced self-attention guided network for multi-stage glaucoma classification using fundus images. Image Vis. Comput. 146: 105042 (2024) - [j31]Pallabi Sharma, Deepak Ranjan Nayak, Bunil Kumar Balabantaray, Muhammad Tanveer
A survey on cancer detection via convolutional neural networks: Current challenges and future directions. Neural Networks 169: 637-659 (2024) - [j30]Dipankar Das
FJA-Net: A Fuzzy Joint Attention Guided Network for Classification of Glaucoma Stages. IEEE Trans. Fuzzy Syst. 32(10): 5438-5448 (2024) - [i5]Dipankar Das, Deepak Ranjan Nayak:
GS-Net: Global Self-Attention Guided CNN for Multi-Stage Glaucoma Classification. CoRR abs/2409.16082 (2024) - 2023
- [j29]Himanshu K. Gajera
A comprehensive analysis of dermoscopy images for melanoma detection via deep CNN features. Biomed. Signal Process. Control. 79(Part): 104186 (2023) - [j28]Himanshu K. Gajera
M2CE: Multi-convolutional neural network ensemble approach for improved multiclass classification of skin lesion. Expert Syst. J. Knowl. Eng. 40(10) (2023) - [j27]Dipankar Das
CA-Net: A Novel Cascaded Attention-Based Network for Multistage Glaucoma Classification Using Fundus Images. IEEE Trans. Instrum. Meas. 72: 1-10 (2023) - [j26]Amogh Manoj Joshi
LiMS-Net: A Lightweight Multi-Scale CNN for COVID-19 Detection from Chest CT Scans. ACM Trans. Manag. Inf. Syst. 14(1): 5:1-5:17 (2023) - [c13]Dipankar Das
GS-Net: Global Self-Attention Guided CNN for Multi-Stage Glaucoma Classification. ICIP 2023: 3454-3458 - 2022
- [j25]Himanshu K. Gajera
Patch-based local deep feature extraction for automated skin cancer classification. Int. J. Imaging Syst. Technol. 32(5): 1774-1788 (2022) - [j24]Partha Pratim Sarangi, Deepak Ranjan Nayak
A feature-level fusion based improved multimodal biometric recognition system using ear and profile face. J. Ambient Intell. Humaniz. Comput. 13(4): 1867-1898 (2022) - [j23]Amogh Manoj Joshi
MFL-Net: An Efficient Lightweight Multi-Scale Feature Learning CNN for COVID-19 Diagnosis From CT Images. IEEE J. Biomed. Health Informatics 26(11): 5355-5363 (2022) - [c12]Himanshu K. Gajera, Mukesh A. Zaveri, Deepak Ranjan Nayak:
Towards Exploring Deep Features for Efficient Melanoma Diagnosis in Dermoscopic Images. OCIT 2022: 146-151 - [c11]Himanshu K. Gajera, Deepak Ranjan Nayak
Fusion of Local and Global Feature Representation With Sparse Autoencoder for Improved Melanoma Classification. EMBC 2022: 5051-5054 - [c10]Tapas Kumar Dutta, Deepak Ranjan Nayak:
CDANet: Channel Split Dual Attention Based CNN for Brain Tumor Classification In Mr Images. ICIP 2022: 4208-4212 - [c9]Snehashis Majhi
Multi-level 3DCNN with Min-Max Ranking Loss for Weakly-Supervised Video Anomaly Detection. ICONIP (7) 2022: 25-37 - [c8]Amogh Manoj Joshi, Deepak Ranjan Nayak
GDenseMNet: Global Dense Multiscale Feature Learning Network for Efficient COVID-19 Detection in CT Images. IJCNN 2022: 1-7 - 2021
- [j22]Si-Yuan Lu, Deepak Ranjan Nayak
A cerebral microbleed diagnosis method via FeatureNet and ensembled randomized neural networks. Appl. Soft Comput. 109: 107567 (2021) - [j21]Soumya Ranjan Nayak, Deepak Ranjan Nayak
Application of deep learning techniques for detection of COVID-19 cases using chest X-ray images: A comprehensive study. Biomed. Signal Process. Control. 64: 102365 (2021) - [j20]Deepak Ranjan Nayak
ECNet: An evolutionary convolutional network for automated glaucoma detection using fundus images. Biomed. Signal Process. Control. 67: 102559 (2021) - [j19]Nikunja Bihari Kar, Deepak Ranjan Nayak
A hybrid feature descriptor with Jaya optimised least squares SVM for facial expression recognition. IET Image Process. 15(7): 1471-1483 (2021) - [j18]Shui-Hua Wang, Deepak Ranjan Nayak
COVID-19 classification by CCSHNet with deep fusion using transfer learning and discriminant correlation analysis. Inf. Fusion 68: 131-148 (2021) - [c7]Himanshu K. Gajera
Improving the Performance of Melanoma Detection in Dermoscopy Images Using Deep CNN Features. AIME 2021: 349-354 - [c6]Snehashis Majhi
Feature Modulating Two-Stream Deep Convolutional Neural Network for Glaucoma Detection in Fundus Images. CVIP (2) 2021: 171-180 - 2020
- [j17]Deepak Ranjan Nayak
A deep stacked random vector functional link network autoencoder for diagnosis of brain abnormalities and breast cancer. Biomed. Signal Process. Control. 58: 101860 (2020) - [j16]Dibyasundar Das
H-WordNet: a holistic convolutional neural network approach for handwritten word recognition. IET Image Process. 14(9): 1794-1805 (2020) - [j15]Deepak Ranjan Nayak
Deep extreme learning machine with leaky rectified linear unit for multiclass classification of pathological brain images. Multim. Tools Appl. 79(21-22): 15381-15396 (2020) - [j14]Dibyasundar Das
MJCN: Multi-objective Jaya Convolutional Network for handwritten optical character recognition. Multim. Tools Appl. 79(43-44): 33023-33042 (2020) - [j13]Deepak Ranjan Nayak
Automated diagnosis of multi-class brain abnormalities using MRI images: A deep convolutional neural network based method. Pattern Recognit. Lett. 138: 385-391 (2020) - [j12]Deepak Ranjan Nayak
Automated Diagnosis of Pathological Brain Using Fast Curvelet Entropy Features. IEEE Trans. Sustain. Comput. 5(3): 416-427 (2020)
2010 – 2019
- 2019
- [j11]Deepak Ranjan Nayak
MJaya-ELM: A Jaya algorithm with mutation and extreme learning machine based approach for sensorineural hearing loss detection. Appl. Soft Comput. 83 (2019) - [j10]Deepak Ranjan Nayak
Application of fast curvelet Tsallis entropy and kernel random vector functional link network for automated detection of multiclass brain abnormalities. Comput. Medical Imaging Graph. 77 (2019) - [j9]Dibyasundar Das
An empirical evaluation of extreme learning machine: application to handwritten character recognition. Multim. Tools Appl. 78(14): 19495-19523 (2019) - [i4]Dibyasundar Das, Deepak Ranjan Nayak, Ratnakar Dash, Banshidhar Majhi:
Backward-Forward Algorithm: An Improvement towards Extreme Learning Machine. CoRR abs/1907.10282 (2019) - 2018
- [j8]Deepak Ranjan Nayak
Combining extreme learning machine with modified sine cosine algorithm for detection of pathological brain. Comput. Electr. Eng. 68: 366-380 (2018) - [j7]Deepak Ranjan Nayak
Discrete ripplet-II transform and modified PSO based improved evolutionary extreme learning machine for pathological brain detection. Neurocomputing 282: 232-247 (2018) - [j6]Deepak Ranjan Nayak
An Improved Pathological Brain Detection System Based on Two-Dimensional PCA and Evolutionary Extreme Learning Machine. J. Medical Syst. 42(1): 19:1-19:15 (2018) - [j5]Deepak Ranjan Nayak
Pathological brain detection using curvelet features and least squares SVM. Multim. Tools Appl. 77(3): 3833-3856 (2018) - [j4]Deepak Ranjan Nayak
Development of pathological brain detection system using Jaya optimized improved extreme learning machine and orthogonal ripplet-II transform. Multim. Tools Appl. 77(17): 22705-22733 (2018) - [c5]Deepak Ranjan Nayak
SCA-RELM: A New Regularized Extreme Learning Machine Based on Sine Cosine Algorithm for Automated Detection of Pathological Brain. RO-MAN 2018: 764-769 - 2017
- [j3]Deepak Ranjan Nayak
Automated pathological brain detection system: A fast discrete curvelet transform and probabilistic neural network based approach. Expert Syst. Appl. 88: 152-164 (2017) - [c4]Deepak Ranjan Nayak
Pathological Brain Detection using Extreme Learning Machine Trained with Improved Whale Optimization Algorithm. ICAPR 2017: 1-6 - 2016
- [j2]Deepak Ranjan Nayak
Brain MR image classification using two-dimensional discrete wavelet transform and AdaBoost with random forests. Neurocomputing 177: 188-197 (2016) - [j1]Deepak Ranjan Nayak
Non-linear cellular automata based edge detector for optical character images. Simul. 92(9): 849-859 (2016) - 2015
- [c3]Deepak Ranjan Nayak
Classification of brain MR images using discrete wavelet transform and random forests. NCVPRIPG 2015: 1-4 - 2014
- [i3]Deepak Ranjan Nayak, Sumit Kumar Sahu, Jahangir Mohammed:
A Cellular Automata based Optimal Edge Detection Technique using Twenty-Five Neighborhood Model. CoRR abs/1402.1348 (2014) - [i2]Deepak Ranjan Nayak, Prashanta Kumar Patra, Amitav Mahapatra:
A Survey on Two Dimensional Cellular Automata and Its Application in Image Processing. CoRR abs/1407.7626 (2014) - 2013
- [i1]Jahangir Mohammed, Deepak Ranjan Nayak:
An Efficient Edge Detection Technique by Two Dimensional Rectangular Cellular Automata. CoRR abs/1312.6370 (2013)
2000 – 2009
Coauthor Index
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