Spatio–Temporal–Spectral Collaborative Learning for Spatio–Temporal Fusion with Land Cover Changes
Author:
Affiliation:
1. Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China
2. College of Electrical and Information Engineering, Hunan University, Changsha, China
Funder
National Natural Science Foundation of China
Zhejiang Provincial Natural Science Foundation of China
Postdoctoral Research Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/9633014/09803281.pdf?arnumber=9803281
Reference50 articles.
1. TEMDnet: A Novel Deep Denoising Network for Transient Electromagnetic Signal With Signal-to-Image Transformation
2. Spatiotemporal Fusion of Land Surface Temperature Based on a Convolutional Neural Network
3. Image Super-Resolution Using Deep Convolutional Networks
4. Spatiotemporal Satellite Image Fusion Using Deep Convolutional Neural Networks
5. Operational Data Fusion Framework for Building Frequent Landsat-Like Imagery
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