Development of a deep learning-based system for automatic screening of turbot (scophthalmus maximus) chronic furunculosis
DOI:
https://doi.org/10.5821/iwp.2025.24.13990Abstract
The sustained growth of the aquaculture industry brings signifi- cant challenges to which artificial intelligence is emerging as an answer. Indeed, improving the detection and management of anomalies and diseases in large fish populations is one of them. In this work, a deep learning-based model has been validated for accurate screening of chronic furunculosis in turbot using a low- cost, scalable and transferable system. The results show a preci- sion of 82% and a processing time below 1s per fish.Downloads
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Copyright (c) 2026 Iván Moreno, Xoel Souto, Gonzalo Rosa, Pedro L. Cebrián, Roberto Bermudez, Miguel Chavarrías, María Isabel Quiroga, Fernando Pescador
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