Transformer and Feature Enhancement for Lightweight Rail Surface Defect Detection
Author:
Affiliation:
1. College of Electronic and Information Engineering, Lanzhou Jiaotong University,Lanzhou,Gansu,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10406301/10408741/10408840.pdf?arnumber=10408840
Reference18 articles.
1. MRSDI-CNN: Multi-Model Rail Surface Defect Inspection System Based on Convolutional Neural Networks
2. An investigation on acoustic emission detection of rail crack in actual application by chaos theory with improved feature detection method
3. Magnetic flux leakage detection method by the arrays consisted of three-dimensional hall sensor for rail top surface cracks
4. Quantitative detection of rail head internal hole defects based on laser ultrasonic bulk wave and optimized variational mode decomposition algorithm
5. Possibilities of Manual Eddy Current Testing for Depth Gaging of Contact-Fatigue Cracks on Rail Rolling Surface
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