1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.CV2025
FedX: Explanation-Guided Pruning for Communication-Efficient Federated Learning in Remote Sensing
Barış Büyüktaş, Jonas Klotz, Begüm Demir
Federated learning (FL) enables the collaborative training of deep neural networks across decentralized data archives (i.e., clients), where each client stores data locally and onl…
cs.CV2025
Communication-Efficient Federated Learning Based on Explanation-Guided Pruning for Remote Sensing Image Classification
Jonas Klotz, Barış Büyüktaş, Begüm Demir
Federated learning (FL) is a decentralized machine learning paradigm in which multiple clients collaboratively train a global model by exchanging only model updates with the centra…
cs.CV2024★ 1 cited
Transformer-based Federated Learning for Multi-Label Remote Sensing Image Classification
Barış Büyüktaş, Kenneth Weitzel, Sebastian Völkers +2
Federated learning (FL) aims to collaboratively learn deep learning model parameters from decentralized data archives (i.e., clients) without accessing training data on clients. Ho…