Complex Crack Segmentation and Quantitative Evaluation of Engineering Materials Based on Deep Learning Methods

Complex Crack Segmentation and Quantitative Evaluation of Engineering Materials Based on Deep Learning Methods

Recognizing and quantifying microcracks on surfaces are crucial for early detection of structural damage, as they can lead to more complex issues in engineering structures. In this study, a dataset reflecting varying surface cracks in various engineering materials from the 2018 Ecuador earthquake wa...

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Bibliographic Details
Main Authors: Xin Jing, Yixuan Huan, Yu Wang, Ruixian Huang, Yang Xu, Qiangqiang Zhang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Complex surface cracks
enhanced U-Net
geometrical quantification
noise reduction
semantic segmentation
structural damage recognition
Online Access:https://ieeexplore.ieee.org/document/10474428/

Internet

https://ieeexplore.ieee.org/document/10474428/

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