Multistage semisupervised active learning framework for crack identification, segmentation, and measurement of bridges-Reference-Cited by-同舟云学术

Multistage semisupervised active learning framework for crack identification, segmentation, and measurement of bridges

Published:2022-06-06 Issue:9 Volume:37 Page:1089-1108
ISSN:1093-9687
Container-title:Computer-Aided Civil and Infrastructure Engineering
language:en
Short-container-title:Computer aided Civil Eng

Author:

Zheng Yue¹²,Gao Yuqing³²,Lu Shiyuan¹,Mosalam Khalid M.³²

Affiliation:

1. Department of Bridge Engineering Tongji University Shanghai China

2. Pacific Earthquake Engineering Research Center University of California Berkeley California USA

3. Department of Civil and Environmental Engineering University of California Berkeley California USA

Publisher

Wiley

Subject

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

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/mice.12851

Reference63 articles.

1. Enhanced probabilistic neural network with local decision circles: A robust classifier

2. A dynamic ensemble learning algorithm for neural networks

3. Encoder–decoder network for pixel‐level road crack detection in black‐box images

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