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
On the Effectiveness of Methods and Metrics for Explainable AI in Remote Sensing Image Scene Classification
Jonas Klotz, Tom Burgert, Begüm Demir
The development of explainable artificial intelligence (xAI) methods for scene classification problems has attracted great attention in remote sensing (RS). Most xAI methods and th…
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…