Two-stage convolutional neural network for road crack detection and segmentation

The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation

(2020) Davide Chicco et al.   BMC GENOMICS

Patch-Based Crack Detection in Black Box Images Using Convolutional Neural Networks

(2019) Somin Park et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

DeepCrack: A deep hierarchical feature learning architecture for crack segmentation

(2019) Yahui Liu et al.   NEUROCOMPUTING

Zernike‐moment measurement of thin‐crack width in images enabled by dual‐scale deep learning

(2018) FuTao Ni et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

(2017) Vijay Badrinarayanan et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

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

Automatic Road Crack Detection Using Random Structured Forests

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

Automatic crack detection from 2D images using a crack measure-based B-spline level set model

(2016) H. N. Nguyen et al.   MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING

Road Crack Detection Using Visual Features Extracted by Gabor Filters

(2013) Eduardo Zalama et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Guided Image Filtering

(2012) Kaiming He et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Learning from Imbalanced Data

(2009) Haibo He et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING