Cost-Effective Fish Volume Estimation in Aquaculture Using Infrared Imaging and Multi-Modal Deep Learning

Sensors 2026 Open access

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Authors: Like Zhang, Yanling Han, Ge Song, Jing Wang, Ping Ma
DOI: 10.3390/s26041221
Cited by: 1
References: 31

Abstract

) of 0.961 for volume estimation, outperforming state-of-the-art methods by 19-41% while reducing hardware costs by 80%. This work advances precision aquaculture by providing robust, deployable tools for feed optimization and health monitoring, promoting environmental sustainability amid rising global seafood demand.

Fields of Study & Subjects

Water Quality Monitoring Technologies Innovations in Aquaponics and Hydroponics Systems Aquaculture disease management and microbiota

Publication details

Journal / source
Sensors
Publisher
MDPI AG
Volume
26
Issue
4
Pages
1221–1221
Publication date
13 February 2026
Language
EN