Pavement Crack Detection Method Based on Deep Learning Models

Automated detection and classification of spilled loads on freeways based on improved YOLO network

(2021) Siqi Zhou et al.   MACHINE VISION AND APPLICATIONS

Autonomous Vision-Based Primary Distribution Systems Porcelain Insulators Inspection Using UAVs

(2021) Ehab Ur Rahman et al.   SENSORS

Ensemble of Deep Convolutional Neural Networks for Automatic Pavement Crack Detection and Measurement

(2020) Zhun Fan et al.   Coatings

Pavement crack detection network based on pyramid structure and attention mechanism

(2020) Xuezhi Xiang et al.   IET Image Processing

RENet: Rectangular convolution pyramid and edge enhancement network for salient object detection of pavement cracks

(2020) Yanyan Wang et al.   MEASUREMENT

Automatic recognition and analysis system of asphalt pavement cracks using interleaved low-rank group convolution hybrid deep network and SegNet fusing dense condition random field

(2020) Gang Li et al.   MEASUREMENT

Joint Graph Optimization and Projection Learning for Dimensionality Reduction

(2019) Yugen Yi et al.   PATTERN RECOGNITION

Non-Negative Matrix Factorization With Locality Constrained Adaptive Graph

(2019) Yugen Yi et al.   IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY

Pixel-Level Cracking Detection on 3D Asphalt Pavement Images Through Deep-Learning- Based CrackNet-V

(2019) Yue Fei et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection

(2019) Fan Yang et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

A novel method for asphalt pavement crack classification based on image processing and machine learning

(2018) Nhat-Duc Hoang et al.   ENGINEERING WITH COMPUTERS

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

Automatic Pixel-Level Crack Detection and Measurement Using Fully Convolutional Network

(2018) Xincong Yang et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

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

(2018) Byunghyun Kim et al.   SENSORS

DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection

(2018) Qin Zou et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

(2017) Shaoqing Ren et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Automatic Road Crack Detection Using Random Structured Forests

(2016) Yong Shi et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

An Automatic Approach for Accurate Edge Detection of Concrete Crack Utilizing 2D Geometric Features of Crack

(2013) Hoang-Nam Nguyen et al.   Journal of Signal Processing Systems for Signal Image and Video Technology

Automatic Road Defect Detection by Textural Pattern Recognition Based on AdaBoost

(2011) Aurélien Cord et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

FoSA: F* Seed-growing Approach for crack-line detection from pavement images

(2011) Qingquan Li et al.   IMAGE AND VISION COMPUTING

Adaptive Road Crack Detection System by Pavement Classification

(2011) Miguel Gavilán et al.   SENSORS

Automatic Pavement Crack Detection Using Texture and Shape Descriptors

(2010) Yong HU et al.   IETE TECHNICAL REVIEW