Comparing Different Deep Learning Architectures as Vision-Based Multi-Label Classifiers for Identification of Multiple Distresses on Asphalt Pavement

Automated Detection and Classification of Pavement Distresses using 3D Pavement Surface Images and Deep Learning

(2021) Rohit Ghosh et al.   TRANSPORTATION RESEARCH RECORD

RoadID: A Dedicated Deep Convolutional Neural Network for Multipavement Distress Detection

(2021) Yishun Li et al.   Journal of Transportation Engineering Part B-Pavements

Pavement distress detection and classification based on YOLO network

(2020) Yuchuan Du et al.   International Journal of Pavement Engineering

Deep learning–based roadway crack classification with heterogeneous image data fusion

(2020) Shanglian Zhou et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Convolutional neural network for pothole detection in asphalt pavement

(2019) Wanli Ye et al.   Road Materials and Pavement Design

Faster region convolutional neural network for automated pavement distress detection

(2019) Liang Song et al.   Road Materials and Pavement Design

Convolutional neural networks based potholes detection using thermal imaging

(2019) Aparna et al.   Journal of King Saud University-Computer and Information Sciences

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

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 classification of pavement crack using deep convolutional neural network

(2018) Baoxian Li et al.   International Journal of Pavement Engineering

Multi-instance multi-label learning

(2011) Zhi-Hua Zhou et al.   ARTIFICIAL INTELLIGENCE

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

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