Using machine vision to estimate fish length from images using regional convolutional neural networks

An image can encode date, time, location and camera information as metadata and implicitly encodes species information and data on human activity, for example the size distribution of fish removals. Accurate length estimates can be made from images using a fiducial marker; however, their manual extr...

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Veröffentlicht in:	Methods in ecology and evolution 2019-12, Vol.10 (12), p.2045-2056
Hauptverfasser:	Monkman, Graham G., Hyder, Kieran, Kaiser, Michel J., Vidal, Franck P., Codling, Edward
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Bias Cameras convolutional neural networks Estimates European sea bass fiducial marker Fish fish length Image classification Learning algorithms Machine learning Machine vision Markers Morphometry Neural networks Outliers (statistics) Particle size distribution photogrammetry regional convolutional neural network Remote monitoring Sea bass Size distribution videogrammetry Vision systems Wildlife management Wildlife surveys
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