Automatic Rail Surface Defect Inspection Using the Pixelwise Semantic Segmentation Model-Reference-Cited by-同舟云学术

Automatic Rail Surface Defect Inspection Using the Pixelwise Semantic Segmentation Model

Author:

Guo Feng¹^ORCID,Qian Yu²^ORCID,Yu Huayang³

Affiliation:

1. Department of Civil and Environmental Engineering, University of South Carolina, Columbia, SC, USA

2. Civil and Environmental Engineering Department, University of South Carolina, Columbia, SC, USA

3. School of Civil Engineering and Transportation, South China University of Technology, Guangdong, Guangzhou, China

Funder

Federal Railroad Administration

National Academy of Science (NAS) through the Innovations Deserving of Exploratory Analysis (IDEA) Program

Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

Reference46 articles.

2. MobileNets: Efficient convolutional neural networks for mobile vision applications;howard;arXiv 1704 04861,2017

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