Work

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

Year: 2026

Type: article

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.

Source: Sensors

DOI: 10.3390/s26041221

Authors: Like Zhang, Yanling Han, Ge Song, Jing Wang, Ping Ma

Institution: Shanghai Ocean University

Language: English

Topic: Water Quality Monitoring Technologies

Subfield: Water Science and Technology

Field: Environmental Science

Domain: Physical Sciences

SDGs: Life below water, Zero hunger

Open Access status: gold

Estimated APC paid: $3,137