Structural crack detection using deep convolutional neural networks
Abstract Convolutional Neural Networks (CNN) have immense potential to solve a broad
range of computer vision problems. It has achieved encouraging results in numerous …
range of computer vision problems. It has achieved encouraging results in numerous …
A survey on generative adversarial networks for imbalance problems in computer vision tasks
Any computer vision application development starts off by acquiring images and data, then
preprocessing and pattern recognition steps to perform a task. When the acquired images …
preprocessing and pattern recognition steps to perform a task. When the acquired images …
Pavement distress detection and classification based on YOLO network
The detection and classification of pavement distress (PD) play a critical role in pavement
maintenance and rehabilitation. Research on PD automation detection and measurement …
maintenance and rehabilitation. Research on PD automation detection and measurement …
A comprehensive study on lane detecting autonomous car using computer vision
Every day, humans make hundreds of decisions, most of which are based on information we
gather from our surroundings. The majority of this perception when it comes to driving is …
gather from our surroundings. The majority of this perception when it comes to driving is …
A field parameters-based method for real-time wear estimation of disc cutter on TBM cutterhead
In hard rock TBM tunneling, the loss caused by disc cutter wear accounts for a large
proportion of time and cost for the entire project. However, existing disc cutter wear …
proportion of time and cost for the entire project. However, existing disc cutter wear …
A fast learning method for accurate and robust lane detection using two-stage feature extraction with YOLO v3
X Zhang, W Yang, X Tang, J Liu - Sensors, 2018 - mdpi.com
To improve the accuracy of lane detection in complex scenarios, an adaptive lane feature
learning algorithm which can automatically learn the features of a lane in various scenarios …
learning algorithm which can automatically learn the features of a lane in various scenarios …
Categorization of post-earthquake damages in RC structural elements with deep learning approach
The aim of this study was to develop an innovative deep learning based intelligent software
(DamageNet) and its mobile applications to classify seismic damage of Reinforced Concrete …
(DamageNet) and its mobile applications to classify seismic damage of Reinforced Concrete …
Deep Learning for Earthquake Disaster Assessment: Objects, Data, Models, Stages, Challenges, and Opportunities
J Jia, W Ye - Remote Sensing, 2023 - mdpi.com
Earthquake Disaster Assessment (EDA) plays a critical role in earthquake disaster
prevention, evacuation, and rescue efforts. Deep learning (DL), which boasts advantages in …
prevention, evacuation, and rescue efforts. Deep learning (DL), which boasts advantages in …
Estimating compressive strength of concrete using deep convolutional neural networks with digital microscope images
Compressive strength is a critical indicator of concrete quality for ensuring the safety of
existing concrete structures. As an alternative to existing nondestructive testing methods …
existing concrete structures. As an alternative to existing nondestructive testing methods …
Deep learning using computer vision in self driving cars for lane and traffic sign detection
Recently, the amount of research in the field of self-driving cars has grown significantly with
autonomous vehicles having clocked in more than 10 million miles, providing a substantial …
autonomous vehicles having clocked in more than 10 million miles, providing a substantial …