Corpus ID: 204788831

A Deep Learning-based Framework for the Detection of Schools of Herring in Echograms

@article{Rezvanifar2019ADL,
  title={A Deep Learning-based Framework for the Detection of Schools of Herring in Echograms},
  author={Alireza Rezvanifar and Tunai Porto Marques and Melissa Cote and Alexandra Branzan Albu and Alex Slonimer and Thomas M. Tolhurst and Kaan Ersahin and Todd Mudge and St{\'e}phane Gauthier},
  journal={ArXiv},
  year={2019},
  volume={abs/1910.08215}
}
Tracking the abundance of underwater species is crucial for understanding the effects of climate change on marine ecosystems. Biologists typically monitor underwater sites with echosounders and visualize data as 2D images (echograms); they interpret these data manually or semi-automatically, which is time-consuming and prone to inconsistencies. This paper proposes a deep learning framework for the automatic detection of schools of herring from echograms. Experiments demonstrated that our… Expand
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