Automatic Detection and Classification of Surface Diseases on Roads and Bridges Using Fuzzy Neural Networks
Author:
Affiliation:
1. Shandong High-speed Rail Transit Group Co Ltd,Yiyang Railway Management Office,Shouguang,Shandong,China,262700
2. Weifang Engineering Vocational College,Qingzhou,Shandong,China,262500
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10539644/10539645/10539783.pdf?arnumber=10539783
Reference14 articles.
1. High-resolution optical inspection system for fast detection and classification of surface defects
2. Automatic defects detection and classification of low carbon steel WAAM products using improved remanence/magneto-optical imaging and cost-sensitive convolutional neural network
3. A cascading fuzzy logic with image processing algorithm–based defect detection for automatic visual inspection of industrial cylindrical object’s surface
4. Automated Detection and Classification of Pavement Distresses using 3D Pavement Surface Images and Deep Learning
5. A Shallow Neural Network for Recognition of Strip Steel Surface Defects Based on Attention Mechanism
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