Conceptual Validation of High-Precision Fish Feeding Behavior Recognition Using Semantic Segmentation and Real-Time Temporal Variance Analysis for Aquaculture

Conceptual Validation of High-Precision Fish Feeding Behavior Recognition Using Semantic Segmentation and Real-Time Temporal Variance Analysis for Aquaculture

Aquaculture plays an important role in the global economy. However, unscientific feeding methods often lead to problems such as feed waste and water pollution. This study aims to address this issue by accurately recognizing fish feeding behaviors to provide automatic bait casting machines with scien...

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Bibliographic Details
Main Authors: Han Kong, Junfeng Wu, Xuelan Liang, Yongzhi Xie, Boyu Qu, Hong Yu
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Biomimetics
Subjects:
fish feeding behavior
semantic segmentation
deep learning
Online Access:https://www.mdpi.com/2313-7673/9/12/730
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