2 papers
cs.CV2026
Label Less, Learn More: Resource-Efficient Active Semi-Supervised Learning for Onboard Satellite Image Annotation
Ahmed Abdelnaby, Mohamed Elmahallawy, Marius Bernahrndt +1
Large-scale pervasive sensing increasingly relies on high-resolution satellite imagery, yet task-specific onboard vision is constrained by costly annotation and limited computation…
cs.LG2026
Resource-Aware Federated Mixture-of-Experts with Adaptive Pruning for Onboard Learning in LEO Satellite Constellations
Mohamed Shaaban, Mohamed Elmahallawy, Marius Bernahrndt +1
Low-Earth-orbit (LEO) satellites are increasingly expected to perform onboard learning for applications such as disaster response and environmental monitoring. However, conventiona…