The CSIRO Crown-of-Thorn Starfish Detection Dataset
This addresses coral reef conservation by providing a dataset for AI-driven COTS detection, but it is incremental as it focuses on data release rather than new methods.
The authors tackled the problem of Crown-of-Thorn Starfish (COTS) outbreaks causing coral loss on the Great Barrier Reef by releasing a large-scale, annotated underwater image dataset to encourage machine learning research for detection and management, resulting in a Kaggle competition to drive development.
Crown-of-Thorn Starfish (COTS) outbreaks are a major cause of coral loss on the Great Barrier Reef (GBR) and substantial surveillance and control programs are underway in an attempt to manage COTS populations to ecologically sustainable levels. We release a large-scale, annotated underwater image dataset from a COTS outbreak area on the GBR, to encourage research on Machine Learning and AI-driven technologies to improve the detection, monitoring, and management of COTS populations at reef scale. The dataset is released and hosted in a Kaggle competition that challenges the international Machine Learning community with the task of COTS detection from these underwater images.