An intelligent method for apparent water leakage segmentation of tunnel lining images considering motion blurs-Reference-Cited by-同舟云学术

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An intelligent method for apparent water leakage segmentation of tunnel lining images considering motion blurs

Published:2025-02-27 Issue: Volume: Page:1-17
ISSN:1749-9518
Container-title:Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards
language:en
Short-container-title:Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards

Author:

Ma Yiding¹,Kong Fanchao²,Lu Dechun¹,Lin Weipeng¹,Zhang Dongmei³,Du Xiuli¹

Affiliation:

1. Beijing University of Technology

2. North China Electric Power University

3. Tongji University

Funder

National Natural Science Foundation of China

National Key R&D Program of China

Beijing Natural Science Foundation

Fundamental Research Funds for the Central Universities

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17499518.2025.2471796

Reference45 articles.

1. Analysis of Edge-Detection Techniques for Crack Identification in Bridges

2. Albluwi, F., V. A. Krylov, and R. Dahyot. 2018. “Image Deblurring and Super-Resolution Using Deep Convolutional Neural Networks.” In 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP), 1–6.

3. Deblurring Images using a Wiener Filter

4. Regularization Preconditioners for Frame-Based Image Deblurring with Reduced Boundary Artifacts

5. Automatic tunnel lining crack evaluation and measurement using deep learning

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