Sea-Scan: High-Accuracy, ML-based Dark Vessel Detection and Localisation via Weakly Supervised DAS Monitoring
Tian Tian, Agastya Raj, Lara Flanagan, John Kennedy, Marco Ruffini
cs.SD cs.LG eess.SP
Abstract
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.
Topics
Classified with taxonomy v2 on Sat, 5 Sept 2026.