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Shaoqing Ren et al.
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Hyunjun Kim et al.
SENSORS (2017)
An adaptive guided wave-Gaussian mixture model for damage monitoring under time-varying conditions: Validation in a full-scale aircraft fatigue test
Lei Qiu et al.
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Deep Convolutional Neural Networks with transfer learning for computer vision-based data-driven pavement distress detection
Kasthurirangan Gopalakrishnan et al.
CONSTRUCTION AND BUILDING MATERIALS (2017)
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Allen Zhang et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2017)
Comparative analysis of image binarization methods for crack identification in concrete structures
Hyunjun Kim et al.
CEMENT AND CONCRETE RESEARCH (2017)
Recognition and evaluation of bridge cracks with modified active contour model and greedy search-based support vector machine
Gang Li et al.
AUTOMATION IN CONSTRUCTION (2017)
Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks
Young-Jin Cha et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2017)
Automated Crack Detection on Concrete Bridges
Prateek Prasanna et al.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (2016)
Automatic Road Crack Detection Using Random Structured Forests
Yong Shi et al.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2016)
A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure
Christian Koch et al.
ADVANCED ENGINEERING INFORMATICS (2015)
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David Lattanzi et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2014)
Automatic Crack Detection and Classification Method for Subway Tunnel Safety Monitoring
Wenyu Zhang et al.
SENSORS (2014)
Automated assessment of cracks on concrete surfaces using adaptive digital image processing
Yufei Liu et al.
SMART STRUCTURES AND SYSTEMS (2014)
In situ damage classification for composite laminates using Gaussian discriminant analysis
Cecilia Larrosa et al.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2014)
An innovative methodology for detection and quantification of cracks through incorporation of depth perception
Mohammad R. Jahanshahi et al.
MACHINE VISION AND APPLICATIONS (2013)
Statistically-based damage detection in geometrically-complex structures using ultrasonic interrogation
Colin Haynes et al.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2013)
Automated image processing technique for detecting and analysing concrete surface cracks
Bang Yeon Lee et al.
STRUCTURE AND INFRASTRUCTURE ENGINEERING (2013)
Fast crack detection method for large-size concrete surface images using percolation-based image processing
Tomoyuki Yamaguchi et al.
MACHINE VISION AND APPLICATIONS (2010)
A survey and evaluation of promising approaches for automatic image-based defect detection of bridge structures
Mohammad R. Jahanshahi et al.
STRUCTURE AND INFRASTRUCTURE ENGINEERING (2009)
Speeded-Up Robust Features (SURF)
Herbert Bay et al.
COMPUTER VISION AND IMAGE UNDERSTANDING (2008)
Improved image analysis for evaluating concrete damage
TC Hutchinson et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2006)
Distinctive image features from scale-invariant keypoints
DG Lowe
INTERNATIONAL JOURNAL OF COMPUTER VISION (2004)
Analysis of edge-detection techniques for crack identification in bridges
L Abdel-Qader et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2003)
Extraction and recognition of artificial text in multimedia documents
C Wolf et al.
PATTERN ANALYSIS AND APPLICATIONS (2003)
Adaptive document image binarization
J Sauvola et al.
PATTERN RECOGNITION (2000)
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