Rail Surface Defect Detection Based on Image Enhancement and Improved YOLOX
During the long and high-intensity railway use, all kinds of defects emerge, which often produce light to moderate damage on the surface, which adversely affects the stable operation of trains and even endangers the safety of travel. Currently, models for detecting rail surface defects are ineffecti...
Main Authors: | Chunguang Zhang, Donglin Xu, Lifang Zhang, Wu Deng |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-06-01
|
Series: | Electronics |
Subjects: | |
Online Access: | https://www.mdpi.com/2079-9292/12/12/2672 |
Similar Items
-
Research On Real-time Detection Algorithm Of Rail-surface Defects Based On Improved YOLOX
by: Yongzhi Min, et al.
Published: (2022-11-01) -
Steel Surface Defect Detection Method Based on Improved YOLOX
by: Chengfei Li, et al.
Published: (2024-01-01) -
LA_YOLOx: Effective Model to Detect the Surface Defects of Insulative Baffles
by: Quanyang Li, et al.
Published: (2023-04-01) -
A 3D Laser Profiling System for Rail Surface Defect Detection
by: Zhimin Xiong, et al.
Published: (2017-08-01) -
Research on steel rail surface defects detection based on improved YOLOv4 network
by: Zengzhen Mi, et al.
Published: (2023-02-01)