VMI-ATN-RCNN: A hybrid deep learning model for fish disease segmentation and classification in aquaculture

Aquaculture is a fast-growing industry in global food production. However, fish disease management is a significant challenge that can severely reduce productivity, yield substantial economic losses, and create major threats to food safety. Accurate disease classification and early diagnosis are cru...

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Veröffentlicht in:	Aquaculture Jg. 611; S. 743047
Hauptverfasser:	Kabitha, P., Nandini, D. Usha
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.01.2026
Schlagworte:	Aquaculture Deep learning Fish disease Multi-scale convolution layer Segmentation and classification Self-adaptive crayfish optimization algorithm Deep learning Multi-scale convolution layer Self-adaptive crayfish optimization algorithm Segmentation and classification Fish disease Aquaculture
ISSN:	0044-8486
Online-Zugang:	Volltext
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