Mohamed Abdel-Nasser
Orcid: 0000-0002-1074-2441
According to our database1,
Mohamed Abdel-Nasser
authored at least 74 papers
between 2014 and 2024.
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Bibliography
2024
Correction: Aggregating efficient transformer and CNN networks using learnable fuzzy measure for breast tumor malignancy prediction in ultrasound images.
Neural Comput. Appl., April, 2024
Aggregating efficient transformer and CNN networks using learnable fuzzy measure for breast tumor malignancy prediction in ultrasound images.
Neural Comput. Appl., April, 2024
FGR-Net: Interpretable fundus image gradeability classification based on deep reconstruction learning.
Expert Syst. Appl., March, 2024
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., January, 2024
2023
Detecting Breast Tumors in Tomosynthesis Images Utilizing Deep Learning-Based Dynamic Ensemble Approach.
Comput., October, 2023
Implicit regularization of a deep augmented neural network model for human motion prediction.
Appl. Intell., July, 2023
Glaucoma Detection in Retinal Fundus Images Based on Deep Transfer Learning and Fuzzy Aggregation Operators.
Int. J. Artif. Intell. Tools, March, 2023
IEEE Access, 2023
2022
Effective Approaches to Fetal Brain Segmentation in MRI and Gestational Age Estimation by Utilizing a Multiview Deep Inception Residual Network and Radiomics.
Entropy, December, 2022
Efficient deep learning-based semantic mapping approach using monocular vision for resource-limited mobile robots.
Neural Comput. Appl., 2022
An Enhanced Scheme for Reducing the Complexity of Pointwise Convolutions in CNNs for Image Classification Based on Interleaved Grouped Filters without Divisibility Constraints.
Entropy, 2022
Automatic Semi-supervised Left Atrial Segmentation Using Deep-Supervision 3DResUnet with Pseudo Labeling Approach for LAScarQS 2022 Challenge.
Proceedings of the Left Atrial and Scar Quantification and Segmentation - First Challenge, 2022
Predicting Personalized Quality of Life of an Intellectually Disabled Person Utilizing Machine Learning.
Proceedings of the Artificial Intelligence Research and Development, 2022
Analyzing the Reliability of Different Machine Radiomics Features Considering Various Segmentation Approaches in Lung Cancer CT Images.
Proceedings of the Artificial Intelligence Research and Development, 2022
A Curated Dataset for Crack Image Analysis: Experimental Verification and Future Perspectives.
Proceedings of the Artificial Intelligence Research and Development, 2022
Transformer-Based Radiomics for Predicting Breast Tumor Malignancy Score in Ultrasonography.
Proceedings of the Artificial Intelligence Research and Development, 2022
Breast Tumor Classification in Digital Tomosynthesis Based on Deep Learning Radiomics.
Proceedings of the Artificial Intelligence Research and Development, 2022
EDBNet: Efficient Dual-Decoder Boosted Network for Eye Retinal Exudates Segmentation.
Proceedings of the Artificial Intelligence Research and Development, 2022
Proceedings of the Artificial Intelligence Research and Development, 2022
Proceedings of the IEEE International Conference on Big Data, 2022
2021
Reliable Solar Irradiance Forecasting Approach Based on Choquet Integral and Deep LSTMs.
IEEE Trans. Ind. Informatics, 2021
Efficient Multi-Organ Multi-Center Cell Nuclei Segmentation Method Based on Deep Learnable Aggregation Network.
Traitement du Signal, 2021
Low-Computational Voltage-Assessment Approach Considering Fine-Resolution Simulations for Distribution Systems With Photovoltaics.
IEEE Syst. J., 2021
Promising Deep Semantic Nuclei Segmentation Models for Multi-Institutional Histopathology Images of Different Organs.
Int. J. Interact. Multim. Artif. Intell., 2021
Expert Syst. Appl., 2021
CoRR, 2021
HIFA: Promising Heterogeneous Solar Irradiance Forecasting Approach Based on Kernel Mapping.
IEEE Access, 2021
Multi-disease, Multi-view and Multi-center Right Ventricular Segmentation in Cardiac MRI Using Efficient Late-Ensemble Deep Learning Approach.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge, 2021
Automatic Segmentation of Head and Neck (H&N) Primary Tumors in PET and CT Images Using 3D-Inception-ResNet Model.
Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2021
Proceedings of the Artificial Intelligence Research and Development, 2021
Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated Branches.
Proceedings of the Artificial Intelligence Research and Development, 2021
Prostate Cancer Delineation in MRI Images Based on Deep Learning: Quantitative Comparison and Promising Perspective.
Proceedings of the Artificial Intelligence Research and Development, 2021
Efficient Fundus Image Gradeability Approach Based on Deep Reconstruction-Classification Network.
Proceedings of the Artificial Intelligence Research and Development, 2021
Lesion Detection in Breast Tomosynthesis Using Efficient Deep Learning and Data Augmentation Techniques.
Proceedings of the Artificial Intelligence Research and Development, 2021
Proceedings of the Artificial Intelligence Research and Development, 2021
Segmenting the Optic Disc Using a Deep Learning Ensemble Model Based on OWA Operators.
Proceedings of the Artificial Intelligence Research and Development, 2021
Proceedings of the Artificial Intelligence Research and Development, 2021
2020
Optimal Voltage Control in Distribution Systems With Intermittent PV Using Multiobjective Grey-Wolf-Lévy Optimizer.
IEEE Syst. J., 2020
Compressive sensing MRI reconstruction using empirical wavelet transform and grey wolf optimizer.
Neural Comput. Appl., 2020
Machine Learning Based Method for Estimating Energy Losses in Large-Scale Unbalanced Distribution Systems with Photovoltaics.
Int. J. Interact. Multim. Artif. Intell., 2020
Breast tumor segmentation in ultrasound images using contextual-information-aware deep adversarial learning framework.
Expert Syst. Appl., 2020
Reliable and Rapid Traffic Congestion Detection Approach Based on Deep Residual Learning and Motion Trajectories.
IEEE Access, 2020
Pectoral Muscle Segmentation in Tomosynthesis Images using Geometry Information and Grey Wolf Optimizer.
Proceedings of the 15th International Joint Conference on Computer Vision, 2020
Channel-wise Aggregation with Self-correction Mechanism for Multi-center Multi-Organ Nuclei Segmentation in Whole Slide Imaging.
Proceedings of the 15th International Joint Conference on Computer Vision, 2020
Detection of Inter Turn Short Circuit Faults in Induction Motor using Artificial Neural Network.
Proceedings of the 26th Conference of Open Innovations Association, 2020
Efficient and Fast Traffic Congestion Classification Based on Video Dynamics and Deep Residual Network.
Proceedings of the Frontiers of Computer Vision - 26th International Workshop, 2020
2019
Neural Comput. Appl., 2019
Adversarial Learning with Multiscale Features and Kernel Factorization for Retinal Blood Vessel Segmentation.
CoRR, 2019
An Efficient Solution for Breast Tumor Segmentation and Classification in Ultrasound Images Using Deep Adversarial Learning.
CoRR, 2019
MobileGAN: Skin Lesion Segmentation Using a Lightweight Generative Adversarial Network.
CoRR, 2019
FCA-Net: Adversarial Learning for Skin Lesion Segmentation Based on Multi-Scale Features and Factorized Channel Attention.
IEEE Access, 2019
FinSeg: Finger Parts Semantic Segmentation using Multi-scale Feature Maps Aggregation of FCN.
Proceedings of the 14th International Joint Conference on Computer Vision, 2019
Proceedings of the Artificial Intelligence Research and Development, 2019
Proceedings of the Artificial Intelligence Research and Development, 2019
Proceedings of the Artificial Intelligence Research and Development, 2019
2018
Aggregating the temporal coherent descriptors in videos using multiple learning kernel for action recognition.
Pattern Recognit. Lett., 2018
Int. J. Interact. Multim. Artif. Intell., 2018
2017
Pattern Recognit. Lett., 2017
Breast tumor classification in ultrasound images using texture analysis and super-resolution methods.
Eng. Appl. Artif. Intell., 2017
Improving the Performance of Diabetic Retinopathy Computer-Aided Diagnosis Systems Using an Ensemble of Texture Analysis Methods.
Proceedings of the Recent Advances in Artificial Intelligence Research and Development, 2017
Feature Learning for Breast Tumour Classification Using Bio-Inspired Optimization Algorithms.
Proceedings of the Recent Advances in Artificial Intelligence Research and Development, 2017
2016
Development of advanced computer methods for breast cancer image interpretation through texture and temporal evolution analysis.
PhD thesis, 2016
Towards cost reduction of breast cancer diagnosis using mammography texture analysis.
J. Exp. Theor. Artif. Intell., 2016
Comput. Methods Programs Biomed., 2016
Exploiting the Kinematic of the Trajectories of the Local Descriptors to Improve Human Action Recognition.
Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016), 2016
Proceedings of the Image Analysis and Recognition - 13th International Conference, 2016
The Impact of Coherence Analysis and Subsequences Aggregation on Representation Learning for Human Activity Recognition.
Proceedings of the Artificial Intelligence Research and Development, 2016
Proceedings of the Artificial Intelligence Research and Development, 2016
Proceedings of the International Conference on Advanced Intelligent Systems and Informatics, 2016
2015
Analysis of tissue abnormality and breast density in mammographic images using a uniform local directional pattern.
Expert Syst. Appl., 2015
Breast Tissue Characterization in X-Ray and Ultrasound Images using Fuzzy Local Directional Patterns and Support Vector Machines.
Proceedings of the VISAPP 2015, 2015
Proceedings of the Artificial Intelligence Research and Development, 2015
2014
Proceedings of the Artificial Intelligence Research and Development, 2014