default search action
Mohamed Abdel-Nasser
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [j33]Saif Khalid
, Hatem A. Rashwan, Saddam Abdulwahab, Mohamed Abdel-Nasser, Facundo Manuel Quiroga
FGR-Net: Interpretable fundus image gradeability classification based on deep reconstruction learning. Expert Syst. Appl. 238(Part C): 121644 (2024) - [j32]Moona Mazher
Deep learning-based survival prediction of brain tumor patients using attention-guided 3D convolutional neural network with radiomics approach from multimodality magnetic resonance imaging. Int. J. Imaging Syst. Technol. 34(1) (2024) - [j31]Loay Hassan
Classifying Breast Tumors in Digital Tomosynthesis by Combining Image Quality-Aware Features and Tumor Texture Descriptors. Mach. Learn. Knowl. Extr. 6(1): 619-641 (2024) - [j30]Vivek Kumar Singh, Ehab Mahmoud Mohamed, Mohamed Abdel-Nasser
Aggregating efficient transformer and CNN networks using learnable fuzzy measure for breast tumor malignancy prediction in ultrasound images. Neural Comput. Appl. 36(11): 5889-5905 (2024) - [j29]Vivek Kumar Singh, Ehab Mahmoud Mohamed, Mohamed Abdel-Nasser:
Correction: Aggregating efficient transformer and CNN networks using learnable fuzzy measure for breast tumor malignancy prediction in ultrasound images. Neural Comput. Appl. 36(11): 5907 (2024) - [i5]Saif Khalid, Hatem A. Rashwan, Saddam Abdulwahab, Mohamed Abdel-Nasser, Facundo Manuel Quiroga, Domenec Puig:
FGR-Net:Interpretable fundus imagegradeability classification based on deepreconstruction learning. CoRR abs/2409.10246 (2024) - 2023
- [j28]Ehab Mahmoud Mohamed
Load Balancing Multi-Player MAB Approaches for RIS-Aided mmWave User Association. IEEE Access 11: 15816-15830 (2023) - [j27]Gaurav Kumar Yadav
Implicit regularization of a deep augmented neural network model for human motion prediction. Appl. Intell. 53(14): 18027-18040 (2023) - [j26]Loay Hassan
Detecting Breast Tumors in Tomosynthesis Images Utilizing Deep Learning-Based Dynamic Ensemble Approach. Comput. 12(11): 220 (2023) - [j25]Mohammed Yousef Salem Ali
Glaucoma Detection in Retinal Fundus Images Based on Deep Transfer Learning and Fuzzy Aggregation Operators. Int. J. Artif. Intell. Tools 32(2): 2340001:1-2340001:28 (2023) - 2022
- [j24]Joao Paulo Schwarz Schuler
An Enhanced Scheme for Reducing the Complexity of Pointwise Convolutions in CNNs for Image Classification Based on Interleaved Grouped Filters without Divisibility Constraints. Entropy 24(9): 1264 (2022) - [j23]Moona Mazher
Effective Approaches to Fetal Brain Segmentation in MRI and Gestational Age Estimation by Utilizing a Multiview Deep Inception Residual Network and Radiomics. Entropy 24(12): 1708 (2022) - [j22]Aditya Singh
Efficient deep learning-based semantic mapping approach using monocular vision for resource-limited mobile robots. Neural Comput. Appl. 34(18): 15617-15631 (2022) - [c37]Ammar M. Okran, Mohamed Abdel-Nasser, Hatem A. Rashwan, Domenec Puig:
Effective Deep Learning-Based Ensemble Model for Road Crack Detection. IEEE Big Data 2022: 6407-6415 - [c36]Gaurav Kumar Yadav
Predicting Personalized Quality of Life of an Intellectually Disabled Person Utilizing Machine Learning. CCIA 2022: 139-142 - [c35]Ammar M. Okran, Mohamed Abdel-Nasser, Hatem A. Rashwan
A Curated Dataset for Crack Image Analysis: Experimental Verification and Future Perspectives. CCIA 2022: 225-228 - [c34]Basma Ahmed, Osama Ahmed Omer, Amal Rashed, Domenec Puig, Mohamed Abdel-Nasser:
Referenceless Image Quality Assessment Utilizing Deep Transfer-Learned Features. CCIA 2022: 243-248 - [c33]Loay Hassan, Mohamed Abdel-Nasser, Adel Saleh, Domenec Puig:
Breast Tumor Classification in Digital Tomosynthesis Based on Deep Learning Radiomics. CCIA 2022: 269-278 - [c32]Maryam Tahmooresi
Analyzing the Reliability of Different Machine Radiomics Features Considering Various Segmentation Approaches in Lung Cancer CT Images. CCIA 2022: 289-297 - [c31]Mohamed A. Hassanien, Vivek Kumar Singh, Domenec Puig, Mohamed Abdel-Nasser:
Transformer-Based Radiomics for Predicting Breast Tumor Malignancy Score in Ultrasonography. CCIA 2022: 298-307 - [c30]Mohammed Yousef Salem Ali, Mohamed Abdel-Nasser, Aïda Valls, Marc Baget, Mohammed Jabreel:
EDBNet: Efficient Dual-Decoder Boosted Network for Eye Retinal Exudates Segmentation. CCIA 2022: 308-317 - [c29]Moona Mazher
Automatic Semi-supervised Left Atrial Segmentation Using Deep-Supervision 3DResUnet with Pseudo Labeling Approach for LAScarQS 2022 Challenge. LAScarQS@MICCAI 2022: 153-161 - 2021
- [j21]Mohamed Abdel-Nasser
HIFA: Promising Heterogeneous Solar Irradiance Forecasting Approach Based on Kernel Mapping. IEEE Access 9: 144906-144915 (2021) - [j20]Md. Mostafa Kamal Sarker
SLSNet: Skin lesion segmentation using a lightweight generative adversarial network. Expert Syst. Appl. 183: 115433 (2021) - [j19]Loay Hassan
Promising Deep Semantic Nuclei Segmentation Models for Multi-Institutional Histopathology Images of Different Organs. Int. J. Interact. Multim. Artif. Intell. 6(6): 35-45 (2021) - [j18]Karar Mahmoud
Low-Computational Voltage-Assessment Approach Considering Fine-Resolution Simulations for Distribution Systems With Photovoltaics. IEEE Syst. J. 15(4): 5321-5331 (2021) - [j17]Loay Hassan
Efficient Multi-Organ Multi-Center Cell Nuclei Segmentation Method Based on Deep Learnable Aggregation Network. Traitement du Signal 38(3): 653-661 (2021) - [j16]Mohamed Abdel-Nasser
Reliable Solar Irradiance Forecasting Approach Based on Choquet Integral and Deep LSTMs. IEEE Trans. Ind. Informatics 17(3): 1873-1881 (2021) - [c28]Eddardaa Ben Loussaief, Mohamed Abdel-Nasser, Domenec Puig:
Prostate Cancer Delineation in MRI Images Based on Deep Learning: Quantitative Comparison and Promising Perspective. CCIA 2021: 295-304 - [c27]Mohammed Yousef Salem Ali, Mohamed Abdel-Nasser, Mohammed Jabreel, Aïda Valls, Marc Baget:
Segmenting the Optic Disc Using a Deep Learning Ensemble Model Based on OWA Operators. CCIA 2021: 305-314 - [c26]Loay Hassan, Mohamed Abdel-Nasser, Adel Saleh, Domenec Puig:
Lesion Detection in Breast Tomosynthesis Using Efficient Deep Learning and Data Augmentation Techniques. CCIA 2021: 315-324 - [c25]Syeda Furruka Banu, Md. Mostafa Kamal Sarker, Mohamed Abdel-Nasser, Hatem A. Rashwan
WEU-Net: A Weight Excitation U-Net for Lung Nodule Segmentation. CCIA 2021: 349-356 - [c24]Basma Ahmed, Mohamed Abdel-Nasser, Osama Ahmed Omer, Amal Rashed, Domenec Puig:
No-Reference Digital Image Quality Assessment Based on Structure Similarity. CCIA 2021: 367-374 - [c23]Joao Paulo Schwarz Schuler, Santiago Romaní
Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated Branches. CCIA 2021: 375-382 - [c22]Joao Paulo Schwarz Schuler, Santiago Romaní
Grouped Pointwise Convolutions Significantly Reduces Parameters in EfficientNet. CCIA 2021: 383-391 - [c21]Saif Khalid
Efficient Fundus Image Gradeability Approach Based on Deep Reconstruction-Classification Network. CCIA 2021: 402-411 - [c20]Abdul Qayyum, Abdesslam Benzinou, Moona Mazher
Automatic Segmentation of Head and Neck (H&N) Primary Tumors in PET and CT Images Using 3D-Inception-ResNet Model. HECKTOR@MICCAI 2021: 58-67 - [c19]Moona Mazher
Multi-disease, Multi-view and Multi-center Right Ventricular Segmentation in Cardiac MRI Using Efficient Late-Ensemble Deep Learning Approach. STACOM@MICCAI 2021: 335-343 - [i4]Syeda Furruka Banu, Md. Mostafa Kamal Sarker, Mohamed Abdel-Nasser, Domenec Puig, Hatem A. Rashwan:
AWEU-Net: An Attention-Aware Weight Excitation U-Net for Lung Nodule Segmentation. CoRR abs/2110.05144 (2021) - 2020
- [j15]Mohamed A. Abdelwahab
Reliable and Rapid Traffic Congestion Detection Approach Based on Deep Residual Learning and Motion Trajectories. IEEE Access 8: 182180-182192 (2020) - [j14]Vivek Kumar Singh, Mohamed Abdel-Nasser
Breast tumor segmentation in ultrasound images using contextual-information-aware deep adversarial learning framework. Expert Syst. Appl. 162: 113870 (2020) - [j13]Karar Mahmoud, Mohamed Abdel-Nasser, Heba Kashef, Domenec Puig, Matti Lehtonen:
Machine Learning Based Method for Estimating Energy Losses in Large-Scale Unbalanced Distribution Systems with Photovoltaics. Int. J. Interact. Multim. Artif. Intell. 6(4): 157-163 (2020) - [j12]Mohamed Ragab
Compressive sensing MRI reconstruction using empirical wavelet transform and grey wolf optimizer. Neural Comput. Appl. 32(7): 2705-2724 (2020) - [j11]Karar Mahmoud
Optimal Voltage Control in Distribution Systems With Intermittent PV Using Multiobjective Grey-Wolf-Lévy Optimizer. IEEE Syst. J. 14(1): 760-770 (2020) - [c18]Mohamed A. Abdelwahab
Efficient and Fast Traffic Congestion Classification Based on Video Dynamics and Deep Residual Network. IW-FCV 2020: 3-17 - [c17]Menshawy Mohamed
Detection of Inter Turn Short Circuit Faults in Induction Motor using Artificial Neural Network. FRUCT 2020: 297-304 - [c16]Mohamed Abdel-Nasser, Adel Saleh, Domenec Puig:
Channel-wise Aggregation with Self-correction Mechanism for Multi-center Multi-Organ Nuclei Segmentation in Whole Slide Imaging. VISIGRAPP (4: VISAPP) 2020: 466-473 - [c15]Mohamed Abdel-Nasser, Francesc Solsona, Domenec Puig:
Pectoral Muscle Segmentation in Tomosynthesis Images using Geometry Information and Grey Wolf Optimizer. VISIGRAPP (5: VISAPP) 2020: 829-836
2010 – 2019
- 2019
- [j10]Vivek Kumar Singh
FCA-Net: Adversarial Learning for Skin Lesion Segmentation Based on Multi-Scale Features and Factorized Channel Attention. IEEE Access 7: 130552-130565 (2019) - [j9]Mohamed Abdel-Nasser
Accurate photovoltaic power forecasting models using deep LSTM-RNN. Neural Comput. Appl. 31(7): 2727-2740 (2019) - [c14]Md. Mostafa Kamal Sarker
Food Places Classification in Egocentric Images Using Siamese Neural Networks. CCIA 2019: 145-151 - [c13]Mohamed Abdel-Nasser
Automated System for Breast Cancer Detection from Electronic Health Records. CCIA 2019: 302-305 - [c12]Vivek Kumar Singh, Mohamed Abdel-Nasser
Mass Detection in Mammograms Using a Robust Deep Learning Model. CCIA 2019: 365-372 - [c11]Adel Saleh, Hatem A. Rashwan
FinSeg: Finger Parts Semantic Segmentation using Multi-scale Feature Maps Aggregation of FCN. VISIGRAPP (5: VISAPP) 2019: 77-84 - [i3]Md. Mostafa Kamal Sarker
MobileGAN: Skin Lesion Segmentation Using a Lightweight Generative Adversarial Network. CoRR abs/1907.00856 (2019) - [i2]Vivek Kumar Singh, Hatem A. Rashwan, Mohamed Abdel-Nasser, Md. Mostafa Kamal Sarker
An Efficient Solution for Breast Tumor Segmentation and Classification in Ultrasound Images Using Deep Adversarial Learning. CoRR abs/1907.00887 (2019) - [i1]Farhan Akram, Vivek Kumar Singh, Hatem A. Rashwan, Mohamed Abdel-Nasser, Md. Mostafa Kamal Sarker
Adversarial Learning with Multiscale Features and Kernel Factorization for Retinal Blood Vessel Segmentation. CoRR abs/1907.02742 (2019) - 2018
- [j8]Mohamed Abdel-Nasser
A Novel Smart Grid State Estimation Method Based on Neural Networks. Int. J. Interact. Multim. Artif. Intell. 5(1): 92-100 (2018) - [j7]Adel Saleh
Aggregating the temporal coherent descriptors in videos using multiple learning kernel for action recognition. Pattern Recognit. Lett. 105: 4-12 (2018) - 2017
- [j6]Mohamed Abdel-Nasser
Breast tumor classification in ultrasound images using texture analysis and super-resolution methods. Eng. Appl. Artif. Intell. 59: 84-92 (2017) - [j5]Mohamed Abdel-Nasser
Analyzing the evolution of breast tumors through flow fields and strain tensors. Pattern Recognit. Lett. 93: 162-171 (2017) - [c10]Shimaa Ragab, Mohamed Abdel-Nasser
Improving the Performance of Diabetic Retinopathy Computer-Aided Diagnosis Systems Using an Ensemble of Texture Analysis Methods. CCIA 2017: 16-25 - [c9]Mohamed Abdel-Nasser
Feature Learning for Breast Tumour Classification Using Bio-Inspired Optimization Algorithms. CCIA 2017: 106-115 - 2016
- [b1]Mohamed Abdel-Nasser:
Development of advanced computer methods for breast cancer image interpretation through texture and temporal evolution analysis. University of Rovira i Virgili, Spain, 2016 - [j4]Mohamed Abdel-Nasser
Temporal mammogram image registration using optimized curvilinear coordinates. Comput. Methods Programs Biomed. 127: 1-14 (2016) - [j3]Mohamed Abdel-Nasser
Automatic nipple detection in breast thermograms. Expert Syst. Appl. 64: 365-374 (2016) - [j2]Mohamed Abdel-Nasser
Towards cost reduction of breast cancer diagnosis using mammography texture analysis. J. Exp. Theor. Artif. Intell. 28(1-2): 385-402 (2016) - [c8]Mohamed Abdel-Nasser
Ultrasound Image Enhancement Using a Deep Learning Architecture. AISI 2016: 639-649 - [c7]Adel Saleh, Mohamed Abdel-Nasser
The Impact of Coherence Analysis and Subsequences Aggregation on Representation Learning for Human Activity Recognition. CCIA 2016: 64-70 - [c6]Mohamed Abdel-Nasser
Modeling the Evolution of Breast Skin Temperatures for Cancer Detection. CCIA 2016: 117-126 - [c5]Adel Saleh, Mohamed Abdel-Nasser
Analysis of Temporal Coherence in Videos for Action Recognition. ICIAR 2016: 325-332 - [c4]Adel Saleh, Miguel Ángel García, Farhan Akram, Mohamed Abdel-Nasser, Domenec Puig:
Exploiting the Kinematic of the Trajectories of the Local Descriptors to Improve Human Action Recognition. VISIGRAPP (3: VISAPP) 2016: 182-187 - 2015
- [j1]Mohamed Abdel-Nasser
Analysis of tissue abnormality and breast density in mammographic images using a uniform local directional pattern. Expert Syst. Appl. 42(24): 9499-9511 (2015) - [c3]Mohamed Abdel-Nasser
Analysis of the evolution of breast tumours using strain tensors. CCIA 2015: 237-246 - [c2]Mohamed Abdel-Nasser
Breast Tissue Characterization in X-Ray and Ultrasound Images using Fuzzy Local Directional Patterns and Support Vector Machines. VISAPP (1) 2015: 387-394 - 2014
- [c1]Mohamed Abdel-Nasser
Improvement of Mass Detection In Breast X-Ray Images Using Texture Analysis Methods. CCIA 2014: 159-168
Coauthor Index
[j33] [j32] [j31] [i5] [j27] [j26] [j24] [j23] [j22] [c37] [c36] [c35] [c34] [c33] [c32] [c31] [c29] [j20] [j19] [j17] [c28] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [i4] [j14] [j13] [c16] [c15] [j10] [c14] [c13] [c12] [c11] [i3] [i2] [i1] [j7] [j6] [j5] [c10] [c9] [j4] [j3] [j2] [c7] [c6] [c5] [c4] [j1] [c3] [c2] [c1]
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-22 21:17 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: