Sea-Scan: High-Accuracy, ML-based Dark Vessel Detection and Localisation via Weakly Supervised DAS Monitoring
Authors: Tian Tian, Agastya Raj, Lara Flanagan, John Kennedy, Marco Ruffini
Organizations: School of Computer Science and Statistics, IRIS Research Group, ADAPT Research Centre, Trinity College Dublin, Ireland · School of Engineering, ADAPT Research Centre, Trinity College Dublin, Ireland
We present an ML-based vessel detection and localization system, trained with weak supervision from imperfect AIS labels, that achieves a 97.8% detection rate at 1.98% false-trigger rate, successfully identifies dark-vessel events from unlabeled data.