Bootstrapping Rare Object Detection in High-Resolution Satellite Imagery

arXiv:2403.02736v1 Announce Type: new
Abstract: Rare object detection is a fundamental task in applied geospatial machine learning, however is often challenging due to large amounts of high-resolution satellite or aerial imagery and few or no labeled positive samples to start with. This paper addresses the problem of bootstrapping such a rare object detection task assuming there is no labeled data and no spatial prior over the area of interest. We propose novel offline and online cluster-based approaches for sampling patches …

abstract aerial arxiv bootstrapping cs.ai cs.cv detection geospatial machine machine learning object paper positive samples satellite type