Universal target recognition and location of convolutional neural network algorithms are difficult to balance the accuracy and speed requirements.Based on YOLO v 2 convolutional neural network,this paper adopts multi-scale training,network pre-training and k-means dimension clustering optimization methods to propose an improved convolutional neural network algorithm for real-time recognition and location of mechanical parts.In this paper,two kinds of objects,nuts and pads,are used to identify and locate the object.The industrial conveyor belt is taken as the scene.At the same time,the existenc...
