Visual Recognition System for Farmed Animals Based on UAV Live Broadcast Linkage
The efficient recognition of farmed animals is the basis for animal husbandry farms to conduct all kinds of precision breeding.Therefore,it is essential to build a corresponding recognition system to support it.The system designed in this study uses the UAV live broadcast linkage method for sample collection and cruise recognition.This method allows real-time video uploading to the data center and addresses issues such as fewer small targets and occlusion problems compared to ordinary UAV shooting.On this basis,the study selects the YOLOv7 algorithm model to recognize animal behavior and quantity.Furthermore,it optimizes and lightweights the YOLOv7 algorithm model to enhance the recognition accuracy and reduce the system load.Finally,the recognition data is output to the standard interface for convenient calls by various precision breeding programs.The system not only adapts to the scene needs of the farm but also takes into account the efficient operation of the system.It can provide unified data support for implementing diverse precision breeding in the farm and reduce the cost of repeated design and decentralized management.
UAV live broadcastfarmed animalvisual recognitionYOLOv7lightweight
NETL
NSTL
万方数据
