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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Veröffentlicht in:	Computers and electronics in agriculture Jg. 214; S. 108310
Hauptverfasser:	Du, Zhuangzhuang, Xu, Xianbao, Bai, Zhuangzhuang, Liu, Xiaohang, Hu, Yang, Li, Wanchao, Wang, Cong, Li, Daoliang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.11.2023
Schlagworte:	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
Online-Zugang:	Volltext
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