Recognition of rust grade and rust ratio of steel structures based on ensembled convolutional neural network-Reference-Cited by-同舟云学术

Recognition of rust grade and rust ratio of steel structures based on ensembled convolutional neural network

Published:2020-07-09 Issue:10 Volume:35 Page:1160-1174
ISSN:1093-9687
Container-title:Computer-Aided Civil and Infrastructure Engineering
language:en
Short-container-title:Computer‐Aided Civil and Infrastructure Engineering

Author:

Xu Jie¹²,Gui Changqing²,Han Qinghua¹²

Affiliation:

1. Key Laboratory of Earthquake Engineering Simulation and Seismic Resilience of Earthquake Administration and Key Laboratory of Coast Civil Structure and Safety of Ministry of Education Ministry Tianjin University Tianjin China

2. School of Civil Engineering Tianjin University Tianjin China

Funder

National Natural Science Foundation of China

Higher Education Discipline Innovation Project

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.12563

Reference39 articles.

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4. Chen L. C. Papandreou G. Schroff F. &Adam H.(2017).Rethinking atrous convolution for semantic image segmentation. arXiv:1706.05587v3

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