Assessing the health of fish populations relies on determining the length of fish in sample species subsets, in conjunction with other key ecosystem markers; thereby, inferring overall health of communities. Despite attempts to use artificial intelligence (AI) to measure fish, most measurement remains a manual process, often necessitating fish being removed from the water. Overcoming this limitation and potentially harmful int...

Machine-assisted object detection and classification of fish species from Baited Remote Underwater Video Station (BRUVS) surveys using deep learning algorithms presents an opportunity for optimising analysis time and rapid reporting of marine ecosystem statuses. Training object detection algorithms for BRUVS analysis presents significant challenges: the model requires training datasets with bounding boxes already applied ident...