An Automated Pipeline for Image Processing and Data Treatment to Track Activity Rhythms of <i>Paragorgia arborea</i> in Relation to Hydrographic Conditions

Imaging technologies are being deployed on cabled observatory networks worldwide. They allow for the monitoring of the biological activity of deep-sea organisms on temporal scales that were never attained before. In this paper, we customized Convolutional Neural Network image processing to track beh...

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Автори:	Ander Zuazo, Jordi Grinyó, Vanesa López-Vázquez, Erik Rodríguez, Corrado Costa, Luciano Ortenzi, Sascha Flögel, Javier Valencia, Simone Marini, Guosong Zhang, Henning Wehde, Jacopo Aguzzi
Формат:	Artigo
Мова:	Inglês
Опубліковано:	MDPI AG 2020-11-01
Серія:	Sensors
Предмети:	neural network deep-sea cold water coral (CWC) automated video imaging filtering rhythms tides
Онлайн доступ:	https://www.mdpi.com/1424-8220/20/21/6281
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