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Echofilter: A Deep Learning Segmentation Model Improves the Automation, Standardization, and Timeliness for Post-Processing Echosounder Data in Tidal Energy Streams. (arXiv:2202.09648v2 [cs.LG] UPDATED)
cs.CV updates on arXiv.org arxiv.org
Understanding the abundance and distribution of fish in tidal energy streams
is important to assess risks presented by introducing tidal energy devices to
the habitat. However tidal current flows suitable for tidal energy are often
highly turbulent, complicating the interpretation of echosounder data. The
portion of the water column contaminated by returns from entrained air must be
excluded from data used for biological analyses. Application of a single
conventional algorithm to identify the depth-of-penetration of entrained air is
insufficient for …
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