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Found 4 papers, 3 papers with code
The FathomNet2023 Competition Dataset
Creating models that are able to recognize when an image or video sequence contains a new organism, an unusual collection of animals, or is otherwise out-of-sample is critical to fully leverage visual data in the ocean.
A reinforcement learning path planning approach for range-only underwater target localization with autonomous vehicles
Underwater target localization using range-only and single-beacon (ROSB) techniques with autonomous vehicles has been used recently to improve the limitations of more complex methods, such as long baseline and ultra-short baseline systems.
FathomNet: A global image database for enabling artificial intelligence in the ocean
The ocean is experiencing unprecedented rapid change, and visually monitoring marine biota at the spatiotemporal scales needed for responsible stewardship is a formidable task.
FathomNet: An underwater image training database for ocean exploration and discovery
Thousands of hours of marine video data are collected annually from remotely operated vehicles (ROVs) and other underwater assets.
