CDANet: Contextual Detail-Aware Network for High-Spatial-Resolution Remote-Sensing Imagery Shadow Detection
Author:
Affiliation:
1. School of Geography and Information Engineering, China University of Geosciences, Wuhan, China
2. China Construction Third Engineering Bureau, Research Institute of Information Technology, Wuhan, China
Funder
National Natural Science Foundation of China
Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/9633014/09684468.pdf?arnumber=9684468
Reference79 articles.
1. Shadow Detection in Single RGB Images Using a Context Preserver Convolutional Neural Network Trained by Multiple Adversarial Examples
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5. Deep Residual Learning for Image Recognition
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