Hybrid deep learning architecture for rail surface segmentation and surface defect detection-Reference-Cited by-同舟云学术

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Hybrid deep learning architecture for rail surface segmentation and surface defect detection

Published:2021-06-23 Issue:2 Volume:37 Page:227-244
ISSN:1093-9687
Container-title:Computer-Aided Civil and Infrastructure Engineering
language:en
Short-container-title:Computer aided Civil Eng

Author:

Wu Yunpeng¹²,Qin Yong¹,Qian Yu²,Guo Feng²,Wang Zhipeng¹,Jia Limin¹

Affiliation:

1. State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

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

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/mice.12710

Reference77 articles.

1. Neural Networks in Civil Engineering: 1989–2000

2. Perceptron Learning in Engineering Design

3. An Evaluation of RetinaNet on Indoor Object Detection for Blind and Visually Impaired Persons Assistance Navigation

4. Neurocomputing in Civil Infrastructure

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