Research and Application of Multi-Objective Workpiece Classification and Recognition Based on YOLO v5 Model
Year: 2024
Type: article
Abstract: Workpiece recognition is an important application of machine vision in industry. The article proposes a deep learning image recognition method for workpiece recognition and classification. First, the workpiece sample library is established, the model is built using the YOLOv5 algorithm, and the optimal model is obtained after training and parameter tuning; in the process of solving the model, it is tested for the workpiece dataset, and the results show that the model achieves an accuracy of more than 94% in the validation set, and finally, after the validation, the model can be accurately recognized and classified, and it provides effective decision-making support for the actual recognition of the workpiece.
Author: Li Xia
Institution: Tianjin University of Technology and Education
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4407775000