Research on the Application of the Target Detection of Automatic Mower Based on Convolution Algorithm

In order to further improve the accuracy of target detection and the whole efficiency of the automatic mower in China, the convolution algorithm theory was used to design and apply the detection system. On the basis of the structure and operation principle of the whole machine, according to the execution rule flow of convolution algorithm, the target function and the core model of detection were established, the software design and hardware platform were built for the detection system, and the target detection operation test of automatic mower was carried out. The results showed that the automatic mower detection system could realize the target fast classification through the application of convolution algorithm, the target recognition accuracy could reach 96.33% on average, and the image recognition clarity could be increased to 95.90%. The automatic mowing leakage rate was greatly reduced, and the operation efficiency of the whole machine could be increased by more than 10% compared with the previous. The system application design was feasible, which would provide some improvement ideas for the precise depth optimization of the mowing equipment, and also would be a very important practical significance for the development of agricultural image visual recognition discipline.