Noise Interference Reduction in Vision Module of Intelligent Plant Cultivation Robot Using Better Cycle GAN

Abstract

The vision recognition module is one of the very important modules in the normal operation of the intelligent plant cultivation robot. In the original vision module, by improving the original YOLOV3(The algorithm proposed in YOLOv3: An Incremental Improvement), a more excellent YOLOV3 was obtained to recognize plants under normal conditions. However, the improved YOLOV3 does not perform well in the visual recognition process when there is a lot of noise interference. To make the visual recognition module continue to work properly, in this paper, the better Cycle GAN (generative adversarial networks) model is proposed to deal with noise based on three common noises, and finally, through a lot of experiments, it is proved that the improvement has some significance for the vision recognition module, which extends the use of the vision recognition module and makes the intelligent plant cultivation robot avoid the interference of noise.