Translation. Region: Russian Federation –
Source: People's Republic of China in Russian – People's Republic of China in Russian –
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Source: People's Republic of China – State Council News
BEIJING, Jan. 11 (Xinhua) — Chinese scientists have successfully developed a lightweight model for recognizing the behavior of beef cattle in pastures from videos captured by a four-legged robot, improving the efficiency of feeding and herd management.
The lightweight MASM-YOLO model was developed by the Institute of Agricultural Information of the Chinese Academy of Agricultural Sciences, and the related research was published in the journal Computers and Electronics in Agriculture.
Accurate and rapid identification of typical cattle behaviour is fundamental for disease diagnosis, rut monitoring, calving prediction and health assessment.
MASM-YOLO enables accurate detection of various behaviors in complex environments, making it suitable for real-time operation on board a mobile robot.
By integrating a multi-dimensional focusing and extraction network, adaptive metering, and other technologies, MASM-YOLO solves key problems such as strong illumination changes, motion blur, and lens occlusion.
MASM-YOLO provides rapid recognition of six typical beef cattle behaviors, including feeding, resting, and moving, and achieves an optimal balance between recognition accuracy and computational efficiency.
This model provides key technical support for the full-scale development of livestock herding robots. -0-
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