Unsupervised underwater shipwreck detection in side-scan sonar images based on domain-adaptive techniques.

Underwater object detection based on side-scan sonar (SSS) suffers from a lack of finely annotated data. This study aims to avoid the laborious task of annotation by achieving unsupervised underwater object detection through domain-adaptive object detection (DAOD). In DAOD, there exists a conflict between feature transferability and discriminability, suppressing the detection performance.