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Related Experiment Video

Updated: Dec 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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Automatic Cow Location Tracking System using Ear Tag Visual Analysis.

Thi Thi Zin¹, Moe Zet Pwint¹, Pann Thinzar Seint¹

¹Graduate School of Engineering, University of Miyazaki, Miyazaki 889-2192, Japan.

Sensors (Basel, Switzerland)

|June 27, 2020

Summary

This summary is machine-generated.

This smart farming system uses image processing and YOLO object detection to track individual cows via ear tag analysis. The system accurately identifies cows, enabling better farm management and data collection for improved livestock health.

Keywords:

convolutional neural network digit segmentation ear tag recognition location searching object detector

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Area of Science:

Agricultural Technology
Computer Vision
Animal Science

Background:

Smart farming systems increasingly integrate image processing and 5G for enhanced livestock management.
Individual cow tracking is crucial for monitoring health, genetics, and productivity.

Purpose of the Study:

To develop and validate an individual cow tracking system using visual ear tag analysis.
To enable effective farm management through real-time data acquisition and cow identification.

Main Methods:

Utilized You Only Look Once (YOLO) for head detection and cow positioning.
Implemented image processing for ear tag area identification and digit segmentation.
Employed a convolutional neural network (CNN) classifier for ear tag digit recognition.

Main Results:

Achieved 100% accuracy in head detection.
Reached 92.5% accuracy in ear tag digit recognition.
Successfully demonstrated real-time cow tracking and identification in a farm setting.

Conclusions:

The proposed ear tag visual analysis system offers a highly effective solution for individual cow tracking.
This technology promises significant improvements in farm management, data accuracy, and livestock monitoring.