Deep Learning–Based Enhancement of Motion Blurred UAV Concrete Crack Images-Reference-Cited by-同舟云学术

Deep Learning–Based Enhancement of Motion Blurred UAV Concrete Crack Images

Published:2020-09 Issue:5 Volume:34 Page:04020028
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Liu Yiqing¹,Yeoh Justin K. W.²^ORCID,Chua David K. H.³

Affiliation:

1. Ph.D. Candidate, Dept. of Civil and Environment Engineering, National Univ. of Singapore, Singapore 117576.

2. Lecturer, Dept. of Civil and Environment Engineering, National Univ. of Singapore, Singapore 117576 (corresponding author). ORCID: .

3. Professor, Dept. of Civil and Environment Engineering, National Univ. of Singapore, Singapore 117576.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000907

Reference49 articles.

1. Image-based retrieval of concrete crack properties for bridge inspection

2. Arjovsky M. S. Chintala and L. Bottou. 2017. “Wasserstein generative adversarial networks.” In Proc. Int. Conf. on Machine Learning 214–223. New York: Proceedings of Machine Learning Research.

3. UAV-based automatic generation of high-resolution panorama at a construction site with a focus on preprocessing for image stitching

4. Digital image restoration

5. Solutions of Ill-Posed Problems.

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