Transfer Learning Based Fault Detection Approach for Rail Components
Author:
Affiliation:
1. Firat University,Computer Engineering,Elazig,Turkey
Funder
TUBITAK (The Scientific and Technological Research Council of Turkey)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9743480/9743518/09743539.pdf?arnumber=9743539
Reference18 articles.
1. An Investigation of Railway Fastener Detection Using Image Processing and Augmented Deep Learning
2. A Defect Detection Method for Rail Surface and Fasteners Based on Deep Convolutional Neural Network
3. A hierarchical learning approach for railway fastener detection using imbalanced samples
4. A Method of Classifying Railway Sleepers and Surface Defects in Real Environment
5. Detection and Measurement of Railway Expansion Gap with Image Processing
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