A New Method for Automated Monitoring of Road Pavement Aging Conditions Based on Recurrent Neural Network
Author:
Affiliation:
1. Institute of Remote Sensing and Geographic Information System, Peking University, Beijing, China
2. Department of Geography and Environmental Management, University of Waterloo, Waterloo, Canada
Funder
National Foundation of Natural Science of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/9972869/09896810.pdf?arnumber=9896810
Reference59 articles.
1. Autonomous Structural Visual Inspection Using Region-Based Deep Learning for Detecting Multiple Damage Types
2. Road Damage Detection and Classification Using Deep Neural Networks with Smartphone Images
3. Monitoring Asphalt Pavement Aging and Damage Conditions from Low-Altitude UAV Imagery Based on a CNN Approach
4. A Deep Learning-Based Approach for Road Pothole Detection in Timor Leste
5. Deep Convolutional Neural Networks with transfer learning for computer vision-based data-driven pavement distress detection
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