Advances in camera technologies have made it easier than ever to collect high-quality underwater imagery, allowing researchers to apply image analysis techniques in many areas of fisheries science, including population assessments and ecological and behavioural studies. This greater ability to capture imagery has resulted in high-volume datasets being collected on a regular basis. As these data are often too large for any team of researchers to analyse fully, researchers have employed-turned their attention to machine learning (ML) as a way of automating tasks (e.g. detection and classification of fishes) that would otherwise require many hours to complete. Machine learning is a branch of artificial intelligence (AI) and computer science which uses data and algorithms to improve performance of a given task, for example, detecting fish in an image.
An aggregation of orange roughy (Hoplostethus atlanticus) on St Helens Seamount, Tasmania, taken at 850 m depth by CSIRO’s acoustic optical system (AOS).