"Smart Aquarium"
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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
NHCE
Abstract
In intensive aquaculture, the real-time detection and monitoring of common infectious disease is an
important basis for scientific fish epidemic prevention strategies that can effectively reduce fish mortality
and economic loss. However, low-quality underwater images and low-identification targets present great
challenges to diseased fish detection. To overcome these challenges, this paper proposes a diseased fish
detection model, using an YOLOV5 network for aquaculture.