Enhanced detection of Argulus and epizootic ulcerative syndrome in fish aquaculture through an improved deep learning model.

Journal: Journal of aquatic animal health
Published Date: Jul 15, 2025

Abstract

OBJECTIVE: Fish disease in aquaculture is a major risk to food safety. The identification of infected fish and disease categories present in fish farms remains difficult to determine at an early stage. Detecting infected fish in time is an essential step in preventing the spread of disease. The aim of this work was to detect fish infected with epizootic ulcerative syndrome and fish lice Argulus spp.

Authors

  • Mahdi Hamzaoui
    Innov'COM Laboratory, Higher School of Communication of Tunis, University of Carthage, Raoued, Ariana, Tunisia.
  • Mohamed Ould-Elhassen Aoueileyine
    Innov'COM Laboratory, Higher School of Communication of Tunis, University of Carthage, Raoued, Ariana, Tunisia.
  • Seifeddine Bouallegue
    University of Doha for Science and Technology, Doha, Qatar.
  • Ridha Bouallegue
    Innov'COM Laboratory High School of Communications (Sup'COM), University of Carthage, Carthage, Tunisia.

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