Industrial UAV-Based Unsupervised Domain Adaptive Crack Recognitions: From Database Towards Real-Site Infrastructural Inspections
Author:
Affiliation:
1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong
Funder
Hong Kong Centre for Logistics Robotics
Hong Kong PhD Fellowship Scheme
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/41/10091710/09900135.pdf?arnumber=9900135
Reference54 articles.
1. DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection
2. High Precision Calibration for Three-Dimensional Vision-Guided Robot System
3. MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection
4. CrackTree: Automatic crack detection from pavement images
5. Highway Crack Segmentation From Unmanned Aerial Vehicle Images Using Deep Learning
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