The Marine Debris Forward-Looking Sonar Datasets
Valdenegro-Toro, Matias, Padmanabhan, Deepan Chakravarthi, Singh, Deepak, Wehbe, Bilal, Petillot, Yvan
–arXiv.org Artificial Intelligence
Sonar sensing is fundamental for underwater robotics, but limited by capabilities of AI systems, which need large training datasets. Public data in sonar modalities is lacking. This paper presents the Marine Debris Forward-Looking Sonar datasets, with three different settings (watertank, turntable, flooded quarry) increasing dataset diversity and multiple computer vision tasks: object classification, object detection, semantic segmentation, patch matching, and unsupervised learning. We provide full dataset description, basic analysis and initial results for some tasks. We expect the research community will benefit from this dataset, which is publicly available at https://doi.org/10.5281/zenodo.15101686
arXiv.org Artificial Intelligence
Mar-28-2025
- Country:
- Europe
- Germany > Bremen
- Bremen (0.04)
- Netherlands > Groningen (0.04)
- United Kingdom > Scotland
- City of Edinburgh > Edinburgh (0.04)
- Germany > Bremen
- North America > United States
- California > San Diego County
- San Diego (0.04)
- Oregon > Marion County
- Four Corners (0.04)
- California > San Diego County
- Europe
- Genre:
- Research Report (0.64)
- Technology: