Unsupervised domain adaptation (UDA) and domain generalization (DG) enable machine
learning models trained on a source domain to perform well on unlabeled or even unseen …

This review article comprehensively delves into the rapidly evolving field of domain
adaptation in computer and robotic vision. It offers a detailed technical analysis of the …

Out-of-Distribution (OOD) detection in computer vision is a crucial research area, with
related benchmarks playing a vital role in assessing the generalizability of models and their …

Robotic waste sorting poses significant challenges in both perception and manipulation,
given the extreme variability of objects that should be recognized on a cluttered conveyor …

Federated Learning has gained significant attention as a data protecting paradigm for
decentralized, clientside learning in the era of interconnected, sensor-equipped edge …

The increase in non-biodegradable waste is a worldwide concern. Recycling facilities play a
crucial role, but their automation is hindered by the complex characteristics of waste …