SenGLEAN: An End-to-End Deep Learning Approach for Super-Resolution of Sentinel-2 Multiresolution Multispectral Images
Author:
Affiliation:
1. Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur, India
2. Department of Geodesy and Geomatics Engineering, University of New Brunswick, Fredericton, Canada
Funder
Mitacs
Natural Sciences and Engineering Research Council of Canada
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/36/10354519/10462214.pdf?arnumber=10462214
Reference59 articles.
1. The effect of fusing Sentinel-2 bands on land-cover classification
2. Super-resolution enhancement of Sentinel-2 image for retrieving LAI and chlorophyll content of summer corn
3. Detailed urban surface characterization using spectra from enhanced spatial resolution Sentinel-2 imagery and a hierarchical multiple endmember spectral mixture analysis approach
4. Satellite Remote Sensing Data for Decision Support in Emerging Agricultural Economies: How Satellite Data Can Transform Agricultural Decision Making [Perspectives]
5. Flood disaster response and decision-making support system based on remote sensing and GIS
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