Interpretability Analysis of Convolutional Neural Networks for Crack Detection

Interpretability Analysis of Convolutional Neural Networks for Crack Detection

Crack detection is an important task in bridge health monitoring, and related detection methods have gradually shifted from traditional manual methods to intelligent approaches with convolutional neural networks (CNNs) in recent years. Due to the opaque process of training and operating CNNs, if the...

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Bibliographic Details
Main Authors: Jie Wu, Yongjin He, Chengyu Xu, Xiaoping Jia, Yule Huang, Qianru Chen, Chuyue Huang, Armin Dadras Eslamlou, Shiping Huang
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Buildings
Subjects:
structural health monitoring
crack detection
interpretability analysis
convolutional neural network
Online Access:https://www.mdpi.com/2075-5309/13/12/3095

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https://www.mdpi.com/2075-5309/13/12/3095

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