Research and Application of Multi-Objective Workpiece Classification and Recognition Based on YOLO v5 Model
International Journal of Computer Science and Information Technology, (2024), Vol.4, No.3, pp.360-366
Published: December 21, 2024
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.
Keywords:
Artifact recognition, YOLOV5, Deep learning
APA Citation:
Li Xia (2024). Research and Application of Multi-Objective Workpiece Classification and Recognition Based on YOLO v5 Model. International Journal of Computer Science and Information Technology, 4(3), 360-366. https://doi.org/10.62051/ijcsit.v4n3.40
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