ArticleJournal of imaging2023
Threshold-Based BRISQUE-Assisted Deep Learning for Enhancing Crack Detection in Concrete Structures.
Article in Journal of imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Improved 3D reconstruction pipeline for enhancing the quality of 3D model generation from multi-view images.Scientific reports · 2025Article
- Optimizing Deep Learning-Based Crack Detection Using No-Reference Image Quality Assessment in a Mobile Tunnel Scanning System.Sensors (Basel, Switzerland) · 2025Article
- Directional Lighting-Based Deep Learning Models for Crack and Spalling Classification.Journal of imaging · 2025Article
- Quality Assessment of High-Speed Motion Blur Images for Mobile Automated Tunnel Inspection.Sensors (Basel, Switzerland) · 2025Article
- Advanced smart assistance with enhancing social interaction and daily activities for visually impaired individuals using deep learning with modified seagull optimization.Scientific reports · 2025Article
- Enhancing Historical Aerial Photographs: A New Approach Based on Non-Reference Metric and Photo Interpretation Elements.Sensors (Basel, Switzerland) · 2025Article
- Optimising Concrete Crack Detection: A Study of Transfer Learning with Application on Nvidia Jetson Nano.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Automated visual inspection has made significant advancements in the detection of cracks on the surfaces of concrete structures. However, low-quality images significantly affect the classification performance of convolutional neural networks (CNNs). Therefore, it is essential to evaluate the suitability of image datasets used in deep learning models, like Visual Geometry Group 16 (VGG16), for accurate crack detection. This study explores the sensitivity of the BRISQUE method to different types of image degradations, such as Gaussian noise and Gaussian blur. By evaluating the performance of the VGG16 model on these degraded datasets with varying levels of noise and blur, a correlation is established between image degradation and BRISQUE scores. The results demonstrate that images with lower BRISQUE scores achieve higher accuracy, F1 score, and Matthew's correlation coefficient (MCC) in crack classification. The study proposes the implementation of a BRISQUE score threshold (B
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.