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Related Experiment Video

Updated: Feb 14, 2026

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

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Published on: November 11, 2022

Cattle Farming Activity Monitoring Using Advanced Deep Learning Approach.

Muhammad Asim¹, Bareera Anam¹, Muhammad Nadeem Ali¹

¹Department of Software & Communications Engineering, Hongik University, Sejong City 30016, Republic of Korea.

Sensors (Basel, Switzerland)

|February 13, 2026

Summary

This summary is machine-generated.

This study presents a vision-based system for monitoring cattle behavior, overcoming limitations of traditional sensors. The computer vision approach accurately identifies fine-grained activities like estrus detection in dairy cows.

Keywords:

activity monitoring animal welfare camera dairy cow deep learning video

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Published on: April 22, 2020

Area of Science:

Agricultural Technology
Computer Vision
Animal Science

Background:

Sensor-based cattle monitoring faces challenges including high costs, animal discomfort, and inaccurate measurements.
Existing methods often lack the granularity needed for precise health and estrus management.

Purpose of the Study:

To introduce and evaluate a vision-based cattle activity monitoring system.
To analyze fine-grained cattle behaviors including estrus detection using deep learning.
To compare the performance of YOLOv8 and YOLOv9 algorithms in this context.

Main Methods:

Deployment of overhead cameras on a commercial dairy farm to capture unconstrained herd behavior.
Creation of a custom dataset with 2956 images annotated into four behaviors: standing, lying, grazing, and estrus.
Application of deep learning algorithms (YOLOv8 and YOLOv9) for behavior classification.

Main Results:

YOLOv8-L achieved a mean Average Precision (mAP) of 91.11%.
YOLOv9-E achieved a mAP of 90.23%.
The vision-based system demonstrated effectiveness in analyzing fine-grained cattle activities under variable farm conditions.

Conclusions:

Vision-based monitoring offers a viable alternative to sensor-based systems in cattle farming.
Deep learning models, particularly YOLOv8, show high accuracy in classifying detailed cattle behaviors for improved herd management and estrus detection.