Related references
Note: Only part of the references are listed.A novel hybrid intelligent model of support vector machines and the MultiBoost ensemble for landslide susceptibility modeling
Binh Thai Pham et al.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT (2019)
A novel method for asphalt pavement crack classification based on image processing and machine learning
Nhat-Duc Hoang et al.
ENGINEERING WITH COMPUTERS (2019)
Crack and Noncrack Classification from Concrete Surface Images Using Machine Learning
Hyunjun Kim et al.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2019)
Predicting earthquake-induced soil liquefaction based on a hybridization of kernel Fisher discriminant analysis and a least squares support vector machine: a multi-dataset study
Nhat-Duc Hoang et al.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT (2018)
Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)
Bahareh Kalantar et al.
GEOMATICS NATURAL HAZARDS & RISK (2018)
Image analysis method for crack distribution and width estimation for reinforced concrete structures
Yuan-Sen Yang et al.
AUTOMATION IN CONSTRUCTION (2018)
Structural Load Estimation Using Machine Vision and Surface Crack Patterns for Shear-Critical RC Beams and Slabs
Rouzbeh Davoudi et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2018)
Automated Pavement Patch Detection and Quantification Using Support Vector Machines
Georgios M. Hadjidemetriou et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2018)
Deterioration Assessment of Infrastructure Using Fuzzy Logic and Image Processing Algorithm
Haran Pragalath et al.
JOURNAL OF PERFORMANCE OF CONSTRUCTED FACILITIES (2018)
Automatic Recognition of Asphalt Pavement Cracks Based on Image Processing and Machine Learning Approaches: A Comparative Study on Classifier Performance
Nhat-Duc Hoang et al.
MATHEMATICAL PROBLEMS IN ENGINEERING (2018)
Automatic Task Classification via Support Vector Machine and Crowdsourcing
Hyungsik Shin et al.
MOBILE INFORMATION SYSTEMS (2018)
A Study on Crack Depth Measurement in Steel Structures Using Image-Based Intensity Differences
Ju-Yeong Jung et al.
ADVANCES IN CIVIL ENGINEERING (2018)
Detection of Surface Crack in Building Structures Using Image Processing Technique with an Improved Otsu Method for Image Thresholding
Nhat-Duc Hoang
ADVANCES IN CIVIL ENGINEERING (2018)
An Artificial Intelligence Method for Asphalt Pavement Pothole Detection Using Least Squares Support Vector Machine and Neural Network with Steerable Filter-Based Feature Extraction
Nhat-Duc Hoang
ADVANCES IN CIVIL ENGINEERING (2018)
Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete
Sattar Dorafshan et al.
CONSTRUCTION AND BUILDING MATERIALS (2018)
Crack detection using image processing: A critical review and analysis
Arun Mohan et al.
ALEXANDRIA ENGINEERING JOURNAL (2018)
A comparative study of landslide susceptibility maps produced using support vector machine with different kernel functions and entropy data mining models in China
Wei Chen et al.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT (2018)
Autonomous Structural Visual Inspection Using Region-Based Deep Learning for Detecting Multiple Damage Types
Young-Jin Cha et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2018)
Multi-level hybrid support vector machine and extreme learning machine based on modified K-means for intrusion detection system
Wathiq Laftah Al-Yaseen et al.
EXPERT SYSTEMS WITH APPLICATIONS (2017)
Remote sensing image classification based on the optimal support vector machine and modified binary coded ant colony optimization algorithm
Mingwei Wang et al.
INFORMATION SCIENCES (2017)
Automatic Pavement-Crack Detection and Segmentation Based on Steerable Matched Filtering and an Active Contour Model
Shuai Li et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2017)
Predicting Safety Risks in Deep Foundation Pits in Subway Infrastructure Projects: Support Vector Machine Approach
Ying Zhou et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2017)
Efficient pavement crack detection and classification
A. Cubero-Fernandez et al.
EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING (2017)
Ambient Air Quality Classification by Grey Wolf Optimizer Based Support Vector Machine
Akash Saxena et al.
JOURNAL OF ENVIRONMENTAL AND PUBLIC HEALTH (2017)
Detection of fatigue cracking in steel bridge girders: A support vector machine approach
Hassene Hasni et al.
ARCHIVES OF CIVIL AND MECHANICAL ENGINEERING (2017)
Machine vision-based model for spalling detection and quantification in subway networks
Thikra Dawood et al.
AUTOMATION IN CONSTRUCTION (2017)
Comparative analysis of image binarization methods for crack identification in concrete structures
Hyunjun Kim et al.
CEMENT AND CONCRETE RESEARCH (2017)
Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks
Young-Jin Cha et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2017)
Image analysis for detection of bugholes on concrete surface
Baoju Liu et al.
CONSTRUCTION AND BUILDING MATERIALS (2017)
Facial expression recognition with automatic segmentation of face regions using a fuzzy based classification approach
Andres Hernandez-Matamoros et al.
KNOWLEDGE-BASED 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)
Localization and Quantification of Concrete Spalling Defects Using Terrestrial Laser Scanning
Min-Koo Kim et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2015)
Achievements and Challenges in Machine Vision-Based Inspection of Large Concrete Structures
C. Koch et al.
ADVANCES IN STRUCTURAL ENGINEERING (2014)
Automatic Crack Detection and Classification Method for Subway Tunnel Safety Monitoring
Wenyu Zhang et al.
SENSORS (2014)
Multiclass from Binary: Expanding One-Versus-All, One-Versus-One and ECOC-Based Approaches
Anderson Rocha et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2014)
Damage assessment on concrete surfaces using multi-spectral image analysis
J. Valenca et al.
CONSTRUCTION AND BUILDING MATERIALS (2013)
Automated image processing technique for detecting and analysing concrete surface cracks
Bang Yeon Lee et al.
STRUCTURE AND INFRASTRUCTURE ENGINEERING (2013)
Rapid entropy-based detection and properties measurement of concrete spalling with machine vision for post-earthquake safety assessments
Stephanie German et al.
ADVANCED ENGINEERING INFORMATICS (2012)
Characterization of Laser Scanners and Algorithms for Detecting Flatness Defects on Concrete Surfaces
Pingbo Tang et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2011)
Detection of large-scale concrete columns for automated bridge inspection
Z. Zhu et al.
AUTOMATION IN CONSTRUCTION (2010)
Image-Based Framework for Concrete Surface Crack Monitoring and Quantification
ZhiQiang Chen et al.
ADVANCES IN CIVIL ENGINEERING (2010)
Improved image analysis for evaluating concrete damage
TC Hutchinson et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2006)
Measuring system for cracks in concrete using multitemporal images
LC Chen et al.
JOURNAL OF SURVEYING ENGINEERING-ASCE (2006)
A comparison of methods for multiclass support vector machines
CW Hsu et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2002)
Share Paper
