Comparative Effectiveness of Data Augmentation Using Traditional Approaches versus StyleGANs in Automated Sewer Defect Detection-Reference-Cited by-同舟云学术

Comparative Effectiveness of Data Augmentation Using Traditional Approaches versus StyleGANs in Automated Sewer Defect Detection

Published:2023-09 Issue:9 Volume:149 Page:
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Zhou Qianqian¹^ORCID,Situ Zuxiang²^ORCID,Teng Shuai³,Chen Gongfa⁴

Affiliation:

1. Associated Professor, School of Civil and Transportation Engineering, Guangdong Univ. of Technology, Waihuan Xi Rd., Guangzhou 510006, China (corresponding author). ORCID: .

2. Master’s Student, School of Civil and Transportation Engineering, Guangdong Univ. of Technology, Waihuan Xi Rd., Guangzhou 510006, China. ORCID: .

3. Ph.D. Candidate, School of Civil and Transportation Engineering, Guangdong Univ. of Technology, Waihuan Xi Rd., Guangzhou 510006, China.

4. Professor, School of Civil and Transportation Engineering, Guangdong Univ. of Technology, Waihuan Xi Rd., Guangzhou 510006, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JWRMD5.WRENG-5831

Reference69 articles.

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2. Automated detection of sewer pipe defects in closed-circuit television images using deep learning techniques

3. Donahue J. Y. Jia O. Vinyals J. Hoffman N. Zhang E. Tzeng and T. Darrell. 2014. “DeCAF: A deep convolutional activation feature for generic visual recognition.” In Proc. Int. Conf. on Machine Learning 647–655. Norfolk MA: Journal of Machine Learning Research.

4. Duran O. K. Althoefer and L. D. Seneviratne. 2002. “Automated sewer pipe inspection through image processing.” In Proc. 2002 IEEE Int. Conf. on Robotics and Automation (Cat. No. 02CH37292) 2551–2556. New York: IEEE.

5. Latent space manipulation for high-resolution medical image synthesis via the StyleGAN

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