Automated pavement distress detection using region based convolutional neural networks

Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection

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

Automatic classification of pavement crack using deep convolutional neural network

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

Deep Learning–Based Fully Automated Pavement Crack Detection on 3D Asphalt Surfaces with an Improved CrackNet

(2018) Allen Zhang et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

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 Crack Detection on Two-Dimensional Pavement Images: An Algorithm Based on Minimal Path Selection

(2016) Rabih Amhaz et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

Deep learning for visual understanding: A review

(2016) Yanming Guo et al.   NEUROCOMPUTING

Selective Search for Object Recognition

(2013) J. R. R. Uijlings et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Automatic Road Defect Detection by Textural Pattern Recognition Based on AdaBoost

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

CrackTree: Automatic crack detection from pavement images

(2011) Qin Zou et al.   PATTERN RECOGNITION LETTERS

ImageNet: Constructing a large-scale image database

(2010) L. Fei-Fei et al.   JOURNAL OF VISION

The Pascal Visual Object Classes (VOC) Challenge

(2009) Mark Everingham et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION