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Presenter: Olav Brautaset, Norwegian Computing Centre
In fisheries acoustics, echo sounding is applied to detect fish and other marine objects in the ocean; a central tool for stock assessments and establishing fishing quotas. Fish detection and species classification from echo sounder data is typically a manual process. In our work, we automate this process by training a convolutional neural network for semantic segmentation using supervised learning. The talk will describe the data, the CNN-approach used for segmentation – as well as issues related to the training data, such as the quality of annotations when used in a machine learning setting.
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