1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.CV2026
Privacy-Preserving Federated Action Recognition via Differentially Private Selective Tuning and Efficient Communication
Idris Zakariyya, Pai Chet Ng, Kaushik Bhargav Sivangi +3
Federated video action recognition enables collaborative model training without sharing raw video data, yet remains vulnerable to two key challenges: \textit{model exposure} and \t…
cs.DC2024★ 1 cited
Leveraging Foundation Models for Efficient Federated Learning in Resource-restricted Edge Networks
S. Kawa Atapour, S. Jamal SeyedMohammadi, S. Mohammad Sheikholeslami +3
Recently pre-trained Foundation Models (FMs) have been combined with Federated Learning (FL) to improve training of downstream tasks while preserving privacy. However, deploying FM…