Multi-Temporal Sentinel-1 SAR Images For Dark Vessel Detection And Classification Using a Circlenet Model

Vessel identification through radar imagery aims to address the complex task of not only detecting, but also classifying ships using SAR images. The goal of the xView3 challenge is to test the capabilities of Sentinel-1 data for the identification of fishing vessels. This initiative plays a crucial role in combating illegal fishing activities and mitigating the associated environmental damage. By fostering advancements in ship classification techniques, the challenge seeks to contribute significantly to global efforts in monitoring and preserving marine ecosystems, particularly by curbing illicit fishing practices.Our paper introduces an end-to-end ship identification method that enhances the challenge-winning CircleNet solution. This improvement is achieved through extending the method for analyzing multi-temporal SAR data, facilitating more robust predictions by effectively filtering out spurious detections of stationary objects.