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The increasing sophistication and availability of Remote Underwater Video Techniques (RUVs), such as remotely operated underwater vehicles and underwater video, are helping researchers overcome the limitations that traditional sampling methods place on acquiring key fisheries parameters, especially in regard to juveniles. RUVs, however, come with their own sets of limitations. In our new paper we evaluate the strengths and limitations of RUVs and investigate how these restrictions can be overcome through the use of Artificial Intelligence, such as Deep Learning.
Is this the future of underwater video sampling?
Read the paper here: Sheaves, M., Bradley, M., Herrera, C., Mattone, C., Lennard C., Sheaves, J, Konovalov, D., 2020. Optimizing video sampling for juvenile fish surveys: Using deep learning and evaluation of assumptions to produce critical fisheries parameters. Fish and Fisheries https://doi.org/10.1111/faf.12501