A REAL-TIME SHEEP COUNTING DETECTION SYSTEM BASED ON MACHINE LEARNING
With the development of modern breeding industry, it is very important to count sheep accurately. In the past, herdsmen used manual statistics to count and manage sheep, which was time-consuming, laborious and often had large errors. In recent years, machine learning methods are widely used in automatic target recognition, which can replace manual labor. This system is based on YOLOv5 algorithm for sheep counting management. The counting of sheep was controlled by two - way counting. This improves the accuracy of counting, saves a lot of manpower and material resources for herdsmen, and greatly promotes the management of animal husbandry.
Abstract in Chinese