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May 28, 2026Scientific Reports0 citationsOpen Access

Vision-Based Framework for Quantifying Fish Feeding Behavior in Aquaculture Systems

A vision-based framework for quantifying fish feeding behavior in industrial recirculating aquaculture systems

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Authors

CHChangrui HuZFZiquan FengYLYuanhang Li

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Overview

Randomized trial utilizes a novel vision-based framework to quantify feeding intensity in aquaculture, indicating significant advancements in feeding technology.

Key Points

  • The aim is to accurately quantify fish feeding intensity in industrial recirculating aquaculture systems to optimize feeding strategies and reduce waste.
  • Developed a hybrid vision-based framework integrating CNN for feature extraction and ViT for context modeling.
  • Incorporated LSTM to analyze temporal dynamics of feeding activity.
  • Constructed a dataset of largemouth bass under industrial RAS conditions with data augmentation to enhance robustness.
  • Achieved over 98% accuracy in classifying four levels of feeding intensity.
  • Outperformed conventional CNN-based methods.
  • Enabled real-time quantitative evaluation of feeding activity for intelligent feeding systems.

Cite This Study

Hu et al. (2026) studied this question.

synapsesocial.com/papers/6a17de003fad632b0f9da7aahttps://doi.org/10.1038/s41598-026-54934-x
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