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Automated detection of Antarctic benthic organisms in high-resolution in situ imagery to aid biodiversity monitoring: optimal model weights
GB/NERC/BAS/PDC/02070

Summary

Abstract:
Model weights for the optimal object detection model, trained on the Weddell Sea Benthic Dataset. Trained 2025-05. Weights should be used with a Deformable-DETR architecture.

This work was funded by the UKRI Future Leaders Fellowship MR/W01002X/1 'The past, present and future of unique cold-water benthic (sea floor) ecosystems in the Southern Ocean' awarded to Rowan Whittle.

Keywords:
Benthos, biodiversity monitoring, computer vision, deep learning, marine ecology

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Citation

Trotter, C., Griffiths, H.J., Khan, T.M., & Whittle, R.J. (2025). Automated detection of Antarctic benthic organisms in high-resolution in situ imagery to aid biodiversity monitoring: optimal model weights (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/b2874f3f-285d-4ae6-9bb4-6bfe3eacbfff

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