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Multi-Target Feeding-Behavior Recognition Method for Cows Based on Improved RefineMask.

Xuwen Li1,2, Ronghua Gao1,2, Qifeng Li1,2

  • 1College of Computer and Information Engineering, Tianjin Agricultural University, Tianjin 300384, China.

Sensors (Basel, Switzerland)
|May 25, 2024
PubMed
Summary

This study introduces an improved RefineMask model for accurate dairy cow feeding behavior recognition. The enhanced model achieves 98.3% accuracy, offering robust visual analysis for livestock management.

Keywords:
RefineMaskbehavioral recognitionfeeding behaviorinstance segmentation

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Area of Science:

  • Agricultural Science
  • Computer Vision
  • Animal Behavior

Background:

  • Current dairy-cattle breeding relies on visual methods for behavior recognition, often limited by low accuracy and high error rates.
  • Accurate monitoring of dairy cow feeding behavior is crucial for understanding feed intake and optimizing herd management.

Purpose of the Study:

  • To develop an advanced visual recognition method for dairy cow feeding behavior using an improved instance-segmentation model.
  • To enhance the accuracy and robustness of detecting and segmenting cow feeding activities in large-scale breeding operations.

Main Methods:

  • An improved RefineMask instance-segmentation model was developed, incorporating convolutional block attention and efficient channel attention modules.
  • The model utilizes GIoU loss for improved bounding box regression accuracy and mask information for foraging behavior recognition.
  • A dataset of 1000 images from 50 dairy cows during peak feeding times was created for training and testing.

Main Results:

  • The improved RefineMask algorithm achieved a 98.3% accuracy in bounding box recognition and segmentation mask determination.
  • This accuracy is 0.7 percentage points higher than benchmark models, with a model size of 49.96 M, suitable for local deployment.
  • The method demonstrated robustness across various scenarios and lighting conditions.

Conclusions:

  • The proposed RefineMask-based method significantly improves the accuracy and reliability of dairy cow feeding behavior recognition.
  • This technology provides valuable technical support for analyzing the relationship between cow feeding behavior and feed intake.
  • The findings contribute to more efficient and data-driven dairy-cattle breeding and management practices.