Defect Detection of Pandrol Track Fastener Based on Local Depth Feature Fusion Network
There are three main problems in track fastener defect detection based on image: (1) The number of abnormal fastener pictures is scarce, and supervised learning detection model is difficult to establish. (2) The potential data features obtained by different feature extraction methods are different....
Saved in:
Main Authors: | Zhaomin Lv, Anqi Ma, Xingjie Chen, Shubin Zheng |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2021/6687146 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Asphalt Mixture for the First Asphalt Concrete Directly Fastened Track in Korea
by: Seong-Hyeok Lee, et al.
Published: (2015-01-01) -
Multi-Scale Feature Fusion Model for Bridge Appearance Defect Detection
by: Rong Pang, et al.
Published: (2024-03-01) -
A System for Robotic Extraction of Fasteners
by: Austin Clark, et al.
Published: (2025-01-01) -
Industrial Printing Image Defect Detection Using Multi-Edge Feature Fusion Algorithm
by: Bangchao Liu, et al.
Published: (2021-01-01) -
Real-Time Depth-Based Hand Detection and Tracking
by: Sung-Il Joo, et al.
Published: (2014-01-01)