mlsanityData to 13 Oct 2026

DarkVesselNet: Multi-Modal Remote Sensing and Trajectory Reasoning for Dark Vessel Detection

arXiv 2606.00445 ↗First posted 30 May 2026cs.CV cs.AI cs.LGcited by 0

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Abstract (arXiv)

Dark vessel detection requires fusing what vessels report through AIS with what satellites observe through radar and optical sensors. DarkVesselNet is a multi-modal remote sensing stack that combines Sentinel-1 SAR, Sentinel-2 optical imagery, geospatial foundation model backbones, AIS trajectory reasoning, TGARD-style gap detection, and a Pi-DPM-inspired anomaly head. The repository exposes the system as a tested Python package and a public Hugging Face Space. The paper presents the sensor stack, backbone abstraction, fusion path, anomaly head, and current validation. The evidence currently available is software-grounded: tests for SAR speckle filtering, optical band ratios, Haversine distance, TGARD gap emission, sensor coregistration, backbone token shapes, and differentiable anomaly scoring.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 20 of its 41 references that are in the map. First posted on arXiv 30 May 2026.

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20 of 41 references.

References · 20

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8 more
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