.png){kind=icon}
.png){kind=icon}
Return
Optimising automatic cattle weight estimation based on computer vision through animal temperament assessment
.png){kind=icon}
OA
AI
DOI：10.1016/j.compag.2025.111395.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• Animal temperament assessment improves automatic cattle weight estimation. • YOLOv8n neural network effectively estimates cattle movement speed. • Adding speed features to morphometric data enhances weight prediction. • ExtraTrees model R2 improved to 0.8450, MAE reduced to 18.01 kg.
Keywords:
Precision Livestock Farming
Computer Vision
Image Analysis
Artificial Intelligence
YOLO
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
8.9
Papers:
9.9K
Citations:
4.8W
Organization
View more organizations