Boosting Semi-Supervised Object Detection in Remote Sensing Images With Active Teaching

arXiv:2402.18958v1 Announce Type: new
Abstract: The lack of object-level annotations poses a significant challenge for object detection in remote sensing images (RSIs). To address this issue, active learning (AL) and semi-supervised learning (SSL) techniques have been proposed to enhance the quality and quantity of annotations. AL focuses on selecting the most informative samples for annotation, while SSL leverages the knowledge from unlabeled samples. In this letter, we propose a novel AL method to boost semi-supervised object detection (SSOD) for remote …

abstract active learning annotations arxiv boosting challenge cs.cv detection images issue quality semi-supervised semi-supervised learning sensing ssl supervised learning teaching type