Binocular Video-Based Automatic Pixel-Level Crack Detection and Quantification Using Deep Convolutional Neural Networks for Concrete Structures

Binocular Video-Based Automatic Pixel-Level Crack Detection and Quantification Using Deep Convolutional Neural Networks for Concrete Structures

Crack detection and quantification play crucial roles in assessing the condition of concrete structures. Herein, a novel real-time crack detection and quantification method that leverages binocular vision and a lightweight deep learning model is proposed. In this methodology, the proposed method bas...

Full description

Saved in:
Bibliographic Details
Main Authors: Liqu Liu, Bo Shen, Shuchen Huang, Runlin Liu, Weizhang Liao, Bin Wang, Shuo Diao
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Buildings
Subjects:
concrete structures
crack detection
EfficientNetV2
binocular vision
crack quantification
deep learning
Online Access:https://www.mdpi.com/2075-5309/15/2/258
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2075-5309/15/2/258

Similar Items