Deep learning-based crack detection and prediction for structural health monitoring

Deep learning-based crack detection and prediction for structural health monitoring

Abstract This study describes a system for real-time crack detection and estimation in constructions, using a proposed model based on CNN, VGG16, U-Net, and Swin Transformer architectures. This model classifies and segments structural cracks irrespective of their severity with 98.88% precision. Prep...

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Bibliographic Details
Main Authors: Satyabrata Roy, Biswarup Yogi, Raj Majumdar, Pritha Ghosh, Sourav Kumar Das
Format: Article
Language:English
Published: Springer 2025-06-01
Series:Discover Applied Sciences
Subjects:
Automated crack detection
CNN
VGG16
U-Net
Swim transformer
Infrastructure protection
Online Access:https://doi.org/10.1007/s42452-025-07272-y
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https://doi.org/10.1007/s42452-025-07272-y

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