Gad Gad

Orcid: 0000-0001-9177-9950

According to our database1, Gad Gad authored at least 12 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
Communication-Efficient and Privacy-Preserving Federated Learning via Joint Knowledge Distillation and Differential Privacy in Bandwidth-Constrained Networks.
IEEE Trans. Veh. Technol., November, 2024

Joint Self-Organizing Maps and Knowledge-Distillation-Based Communication-Efficient Federated Learning for Resource-Constrained UAV-IoT Systems.
IEEE Internet Things J., May, 2024

Combating Malware Traffic in Emerging Networks: A Collaborative Learning Approach.
Proceedings of the International Conference on Smart Applications, 2024

Optimizing VNF Migration in B5G Core Networks: A Machine Learning Approach.
Proceedings of the International Conference on Smart Applications, 2024

Federated Learning With Selective Knowledge Distillation Over Bandwidth-constrained Wireless Networks.
Proceedings of the IEEE International Conference on Communications, 2024

2023
Federated Learning via Augmented Knowledge Distillation for Heterogenous Deep Human Activity Recognition Systems.
Sensors, 2023

An Explainable AI System for Medical Image Segmentation With Preserved Local Resolution: Mammogram Tumor Segmentation.
IEEE Access, 2023

Communication-Efficient Federated Learning in Drone-Assisted IoT Networks: Path Planning and Enhanced Knowledge Distillation Techniques.
Proceedings of the 34th IEEE Annual International Symposium on Personal, 2023

Communication-Efficient Privacy-Preserving Federated Learning via Knowledge Distillation for Human Activity Recognition Systems.
Proceedings of the IEEE International Conference on Communications, 2023

Joint Knowledge Distillation and Local Differential Privacy for Communication-Efficient Federated Learning in Heterogeneous Systems.
Proceedings of the IEEE Global Communications Conference, 2023

Mammogram Tumor Segmentation with Preserved Local Resolution: An Explainable AI System.
Proceedings of the IEEE Global Communications Conference, 2023

2021
Towards Optimized IoT-based Context-aware Video Content Analysis Framework.
Proceedings of the 7th IEEE World Forum on Internet of Things, 2021


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