Artificial intelligence-empowered pipeline for image-based inspection of concrete structures

Anomaly detection of defects on concrete structures with the convolutional autoencoder

(2020) J.K. Chow et al.   ADVANCED ENGINEERING INFORMATICS

Sewer damage detection from imbalanced CCTV inspection data using deep convolutional neural networks with hierarchical classification

(2019) Duanshun Li et al.   AUTOMATION IN CONSTRUCTION

Segmentation-based deep-learning approach for surface-defect detection

(2019) Domen Tabernik et al.   JOURNAL OF INTELLIGENT MANUFACTURING

f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks

(2019) Thomas Schlegl et al.   MEDICAL IMAGE ANALYSIS

A defect classification methodology for sewer image sets with convolutional neural networks

(2019) Dirk Meijer et al.   AUTOMATION IN CONSTRUCTION

Vision-Based Autonomous Crack Detection of Concrete Structures Using a Fully Convolutional Encoder–Decoder Network

(2019) M. M. Manjurul Islam et al.   SENSORS

A deep learning-based framework for an automated defect detection system for sewer pipes

(2019) Xianfei Yin et al.   AUTOMATION IN CONSTRUCTION

Detecting healthy concrete surfaces

(2018) Philipp Hüthwohl et al.   ADVANCED ENGINEERING INFORMATICS

Automated defect classification in sewer closed circuit television inspections using deep convolutional neural networks

(2018) Srinath S. Kumar et al.   AUTOMATION IN CONSTRUCTION

Unified Vision-Based Methodology for Simultaneous Concrete Defect Detection and Geolocalization

(2018) Ruoxing Li et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naïve Bayes Data Fusion

(2018) Fu-Chen Chen et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Automated defect inspection of LED chip using deep convolutional neural network

(2018) Hui Lin et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Automated region-of-interest localization and classification for vision-based visual assessment of civil infrastructure

(2018) Chul Min Yeum et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete

(2018) Sattar Dorafshan et al.   CONSTRUCTION AND BUILDING MATERIALS

Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique

(2018) Byunghyun Kim et al.   SENSORS

Autonomous concrete crack detection using deep fully convolutional neural network

(2018) Cao Vu Dung et al.   AUTOMATION IN CONSTRUCTION

Autonomous image localization for visual inspection of civil infrastructure

(2017) C M Yeum et al.   Smart Materials and Structures

Design of deep convolutional neural network architectures for automated feature extraction in industrial inspection

(2016) Daniel Weimer et al.   CIRP ANNALS-MANUFACTURING TECHNOLOGY

Automated Crack Detection on Concrete Bridges

(2016) Prateek Prasanna et al.   IEEE Transactions on Automation Science and Engineering

Detection crack in image using Otsu method and multiple filtering in image processing techniques

(2016) Ahmed Mahgoub Ahmed Talab et al.   OPTIK

Texture Analysis Based Damage Detection of Ageing Infrastructural Elements

(2012) Michael O’Byrne et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Robust Automated Concrete Damage Detection Algorithms for Field Applications

(2012) David Lattanzi et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

Biochemical attack on concrete in wastewater applications: A state of the art review

(2010) M. O’Connell et al.   CEMENT & CONCRETE COMPOSITES

Fast crack detection method for large-size concrete surface images using percolation-based image processing

(2009) Tomoyuki Yamaguchi et al.   MACHINE VISION AND APPLICATIONS