A Rail Surface Defect Detection Method Based on Pyramid Feature and Lightweight Convolutional Neural Network
Author:
Affiliation:
1. School of Automation Science and Engineering, South China University of Technology, Guangzhou, China
2. School of Underwater Acoustic Engineering, Harbin Engineering University, Harbin, China
Funder
Key Research and Development Program of Guangdong Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/19/9717300/09750081.pdf?arnumber=9750081
Reference30 articles.
1. Pyramid Scene Parsing Network
2. Automatic defect inspection for LCDs using singular value decomposition
3. Texture classification for rail surface condition evaluation
4. A Real-Time Visual Inspection System for Discrete Surface Defects of Rail Heads
5. A Visual Detection System for Rail Surface Defects
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