Feature fusion strategy and improved GhostNet for accurate recognition of fish feeding behavior

•An LC-GhostNet lightweight network based on the GhostNet is proposed.•Fusion of Mel spectrogram, STFT feature map, and CQT feature map.•The method can quantify the feeding behavior of fish into four classes.•The feature fusion accuracy reaches 97.941%, which is higher than a single feature. In aqua...

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Vydáno v:	Computers and electronics in agriculture Ročník 214; s. 108310
Hlavní autoři:	Du, Zhuangzhuang, Xu, Xianbao, Bai, Zhuangzhuang, Liu, Xiaohang, Hu, Yang, Li, Wanchao, Wang, Cong, Li, Daoliang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.11.2023
Témata:	agriculture aquaculture data collection electronics Feature fusion fish Fish feeding intensity LC-GhostNet lightweight network nondestructive methods On-demand feeding system Oplegnathus LC-GhostNet lightweight network Feature fusion Fish feeding intensity On-demand feeding system
ISSN:	0168-1699, 1872-7107
On-line přístup:	Získat plný text
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