1 citations · 2 across the 4 of their papers we have counts for
4 papers
Mutli-Level Autoencoder: Deep Learning Based Channel Coding and Modulation
Ahmad Abdel-Qader, Anas Chaaban, Mohamed S. Shehata
In this paper, we design a deep learning-based convolutional autoencoder for channel coding and modulation. The objective is to develop an adaptive scheme capable of operating at v…
FedPartWhole: Federated domain generalization via consistent part-whole hierarchies
Ahmed Radwan, Mohamed S. Shehata
Federated Domain Generalization (FedDG), aims to tackle the challenge of generalizing to unseen domains at test time while catering to the data privacy constraints that prevent cen…
MedMAE: A Self-Supervised Backbone for Medical Imaging Tasks
Anubhav Gupta, Islam Osman, Mohamed S. Shehata +1
Medical imaging tasks are very challenging due to the lack of publicly available labeled datasets. Hence, it is difficult to achieve high performance with existing deep-learning mo…
Universal Medical Imaging Model for Domain Generalization with Data Privacy
Ahmed Radwan, Islam Osman, Mohamed S. Shehata
Achieving domain generalization in medical imaging poses a significant challenge, primarily due to the limited availability of publicly labeled datasets in this domain. This limita…