Classification of Asphalt Pavement Cracks Using Laplacian Pyramid-Based Image Processing and a Hybrid Computational Approach
Published 2018 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Classification of Asphalt Pavement Cracks Using Laplacian Pyramid-Based Image Processing and a Hybrid Computational Approach
Authors
Keywords
-
Journal
Computational Intelligence and Neuroscience
Volume 2018, Issue -, Pages 1-16
Publisher
Hindawi Limited
Online
2018-10-02
DOI
10.1155/2018/1312787
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Automatic recognition of asphalt pavement cracks using metaheuristic optimized edge detection algorithms and convolution neural network
- (2018) Hoang Nhat-Duc et al. AUTOMATION IN CONSTRUCTION
- Spatial pattern assessment of tropical forest fire danger at Thuan Chau area (Vietnam) using GIS-based advanced machine learning algorithms: A comparative study
- (2018) Nguyen Ngoc Thach et al. Ecological Informatics
- A novel method for asphalt pavement crack classification based on image processing and machine learning
- (2018) Nhat-Duc Hoang et al. ENGINEERING WITH COMPUTERS
- Grey-related least squares support vector machine optimization model and its application in predicting natural gas consumption demand
- (2018) Yong-Hong Wu et al. JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
- Image Processing–Based Classification of Asphalt Pavement Cracks Using Support Vector Machine Optimized by Artificial Bee Colony
- (2018) Nhat-Duc Hoang et al. JOURNAL OF COMPUTING IN CIVIL ENGINEERING
- Biological Flower Pollination Algorithm with Orthogonal Learning Strategy and Catfish Effect Mechanism for Global Optimization Problems
- (2018) Weijia Cui et al. MATHEMATICAL PROBLEMS IN ENGINEERING
- Optimized minimal path selection (OMPS) method for automatic and unsupervised crack segmentation within two-dimensional pavement images
- (2018) Wissam Kaddah et al. VISUAL COMPUTER
- Automatic Pixel-Level Pavement Crack Detection Using Information of Multi-Scale Neighborhoods
- (2018) Dihao Ai et al. IEEE Access
- An Artificial Intelligence Method for Asphalt Pavement Pothole Detection Using Least Squares Support Vector Machine and Neural Network with Steerable Filter-Based Feature Extraction
- (2018) Nhat-Duc Hoang Advances in Civil Engineering
- Optimizing the Prediction Accuracy of Friction Capacity of Driven Piles in Cohesive Soil Using a Novel Self-Tuning Least Squares Support Vector Machine
- (2018) Doddy Prayogo et al. Advances in Civil Engineering
- Cracking Classification Using Minimum Rectangular Cover–Based Support Vector Machine
- (2017) Shaofan Wang et al. JOURNAL OF COMPUTING IN CIVIL ENGINEERING
- Automatic Pavement-Crack Detection and Segmentation Based on Steerable Matched Filtering and an Active Contour Model
- (2017) Shuai Li et al. JOURNAL OF COMPUTING IN CIVIL ENGINEERING
- Recognition of asphalt pavement crack length using deep convolutional neural networks
- (2017) Zheng Tong et al. Road Materials and Pavement Design
- Efficient pavement crack detection and classification
- (2017) A. Cubero-Fernandez et al. EURASIP Journal on Image and Video Processing
- Wavelet-morphology based detection of incipient linear cracks in asphalt pavements from RGB camera imagery and classification using circular Radon transform
- (2016) Yashon O. Ouma et al. ADVANCED ENGINEERING INFORMATICS
- Groutability estimation of grouting processes with cement grouts using Differential Flower Pollination Optimized Support Vector Machine
- (2016) Nhat-Duc Hoang et al. APPLIED SOFT COMPUTING
- Image Based Techniques for Crack Detection, Classification and Quantification in Asphalt Pavement: A Review
- (2016) H. Zakeri et al. ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
- Weighted Neighborhood Pixels Segmentation Method for Automated Detection of Cracks on Pavement Surface Images
- (2016) Lu Sun et al. JOURNAL OF COMPUTING IN CIVIL ENGINEERING
- Using flower pollination algorithm and atomic potential function for shape matching
- (2016) Yongquan Zhou et al. NEURAL COMPUTING & APPLICATIONS
- Comparison of Supervised Classification Techniques for Vision-Based Pavement Crack Detection
- (2016) Soroush Mokhtari et al. TRANSPORTATION RESEARCH RECORD
- Gaussian image pyramid based texture features for classification of microscopic images of hardwood species
- (2015) Arvind R. Yadav et al. OPTIK
- Hybrid ABC-ANN for pavement surface distress detection and classification
- (2015) Anan Banharnsakun International Journal of Machine Learning and Cybernetics
- Automatic Pavement Crack Recognition Based on BP Neural Network
- (2014) Li Li et al. Promet-Traffic & Transportation
- Matched Filtering Algorithm for Pavement Cracking Detection
- (2013) Allen Zhang et al. TRANSPORTATION RESEARCH RECORD
- Multiclass From Binary: Expanding One-Versus-All, One-Versus-One and ECOC-Based Approaches
- (2013) Anderson Rocha et al. IEEE Transactions on Neural Networks and Learning Systems
- Beamlet Transform-Based Technique for Pavement Crack Detection and Classification
- (2010) L. Ying et al. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- JADE: Adaptive Differential Evolution With Optional External Archive
- (2009) Jingqiao Zhang et al. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started