Deep Learning-Based Understanding of Defects in Continuous Casting Product

Deep Learning-Based Understanding of Defects in Continuous Casting Product

A novel YOLOv5 network is presented in this paper to quantify the degree of defects in continuously cast billets. The proposed network addresses the challenges posed by noise or dirty spots and different defect sizes in the images of these billets. The CBAM-YOLOv5 network integrates the channel and...

Full description

Bibliographic Details
Main Authors: Zeyuan Ding, Jingxiao Zhao, Raja Devesh Kuma Misra, Fujian Guo, Zhenjia Xie, Xuelin Wang, Xiucheng Li, Jingliang Wang, Chengjia Shang
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Metals
Subjects:
continuous casting billet
segregation
deep learning
YOLOv5 network
convolutional block attention module
Online Access:https://www.mdpi.com/2075-4701/13/11/1809

Internet

https://www.mdpi.com/2075-4701/13/11/1809

Similar Items