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Related Experiment Video

Updated: May 17, 2025

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus
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Research on Enhanced Dynamic Pig Counting Based on YOLOv8n and Deep SORT.

Peng Shen1, Keyu Mei1, Haori Xue1

  • 1North China Institute of Aerospace Engineering, School of Aeronautics and Astronautics, Langfang 065000, China.

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|May 14, 2025
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Summary

This study introduces an improved YOLOv8n-EGV+Deep SORT-P algorithm for accurate dynamic pig counting in farms. The enhanced model significantly boosts counting accuracy and tracking stability, addressing limitations of manual methods.

Keywords:
Deep SORTYOLOv8nmulti-object trackingobject detectionpig counting

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Area of Science:

  • Agricultural technology
  • Computer vision
  • Animal science

Background:

  • Manual pig counting is labor-intensive and inaccurate.
  • Existing automated methods struggle with detection and tracking challenges like crowding and occlusion.

Purpose of the Study:

  • To develop an enhanced algorithm for accurate and stable dynamic pig counting.
  • To improve pig target recognition and tracking accuracy in real-world farming environments.

Main Methods:

  • Integration of ELA attention, GSConv, and VoVGSCSP modules into YOLOv8n for improved detection.
  • Enhancement of Deep SORT with DenseNet and CIoU for robust tracking.
  • Validation using pig videos from farm passages.

Main Results:

  • The improved YOLOv8n-EGV+Deep SORT-P algorithm achieved 92.1% counting accuracy, a 17.5% improvement.
  • Enhanced Deep SORT-P tracking showed improved MOTA (89.2%) and MOTP (90.4%), with reduced IDSW.
  • The algorithm demonstrated stable dynamic pig counting in practical settings.

Conclusions:

  • The proposed algorithm offers a significant advancement over existing methods for dynamic pig counting.
  • This technology provides valuable data for precision livestock farming and management.
  • The enhanced system addresses key challenges in automated animal counting.