Federated Learning with Heterogeneous Data Handling for Robust Vehicular Object Detection

no code implementations • 2 May 2024 • Ahmad Khalil, Tizian Dege, Pegah Golchin, Rostyslav Olshevskyi, Antonio Fernandez Anta, Tobias Meuser

In this paper, we introduce FedProx+LA, a novel FL method building upon the state-of-the-art FedProx and FedLA to tackle data heterogeneity, which is specifically tailored for vehicular networks.

Autonomous Driving Federated Learning +2

A Comprehensive Study of Vision Transformers in Image Classification Tasks

no code implementations • 2 Dec 2023 • Mahmoud Khalil, Ahmad Khalil, Alioune Ngom

In this paper, we conduct a comprehensive survey of existing papers on Vision Transformers for image classification.

Classification Image Classification