Automatic pixel-level crack segmentation in images using fully convolutional neural network based on residual blocks and pixel local weights

Automated pavement crack detection and segmentation based on two‐step convolutional neural network

(2020) Jingwei Liu et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

CrackGAN: Pavement Crack Detection Using Partially Accurate Ground Truths Based on Generative Adversarial Learning

(2020) Kaige Zhang et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

Deep Learning for Audio Signal Processing

(2019) Hendrik Purwins et al.   IEEE Journal of Selected Topics in Signal Processing

DeepCrack: A deep hierarchical feature learning architecture for crack segmentation

(2019) Yahui Liu et al.   NEUROCOMPUTING

Concrete crack detection using context‐aware deep semantic segmentation network

(2019) Xinxiang Zhang et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Computer vision-based concrete crack detection using U-net fully convolutional networks

(2019) Zhenqing Liu et al.   AUTOMATION IN CONSTRUCTION

Automatic Retinal Blood Vessel Segmentation Based on Fully Convolutional Neural Networks

(2019) Yun Jiang et al.   Symmetry-Basel

Segmentation of casting defect regions for the extraction of microstructural properties

(2019) Jinhua Lin et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Recent Trends in Deep Learning Based Natural Language Processing [Review Article]

(2018) Tom Young et al.   IEEE Computational Intelligence Magazine

Deep variance network: An iterative, improved CNN framework for unbalanced training datasets

(2018) Shuai Li et al.   PATTERN RECOGNITION

Focal loss for dense object detection

(2018) Tsung-Yi Lin et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

MangoNet: A deep semantic segmentation architecture for a method to detect and count mangoes in an open orchard

(2018) Ramesh Kestur et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Medical breast ultrasound image segmentation by machine learning

(2018) Yuan Xu et al.   ULTRASONICS

DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection

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

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

(2017) Vijay Badrinarayanan 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

Deep learning

(2015) Yann LeCun et al.   NATURE

Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool

(2015) Abdel Aziz Taha et al.   BMC MEDICAL IMAGING

Image-based retrieval of concrete crack properties for bridge inspection

(2013) R.S. Adhikari et al.   AUTOMATION IN CONSTRUCTION