Automatic fish species classification in underwater videos: exploiting pre-trained deep neural network models to compensate for limited labelled data

Abstract There is a need for automatic systems that can reliably detect, track and classify fish and other marine species in underwater videos without human intervention. Conventional computer vision techniques do not perform well in underwater conditions where the background is complex and the shap...

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Veröffentlicht in:	ICES journal of marine science 2018-01, Vol.75 (1), p.374-389
Hauptverfasser:	Siddiqui, Shoaib Ahmed, Salman, Ahmad, Malik, Muhammad Imran, Shafait, Faisal, Mian, Ajmal, Shortis, Mark R, Harvey, Euan S
Format:	Artikel
Sprache:	eng
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