DEEP RESIDUAL LEARNING FOR SINGLE-IMAGE SUPER-RESOLUTION OF MULTI-SPECTRAL SATELLITE IMAGERY

8 citations as recorded by crossref.

1. Using Super-Resolution Algorithms for Small Satellite Imagery: A Systematic Review K. Karwowska & D. Wierzbicki 10.1109/JSTARS.2022.3167646
2. The Effect of Super Resolution Method on Classification Performance of Satellite Images A. CENGİZ & D. AVCI 10.55525/tjst.1252420
3. How Does Super-Resolution for Satellite Imagery Affect Different Types of Land Cover? Sentinel-2 Case A. Malczewska & M. Wielgosz 10.1109/JSTARS.2023.3328997
4. Super-Resolution of Sentinel-2 Images Using a Spectral Attention Mechanism M. Zabalza & A. Bernardini 10.3390/rs14122890
5. A comprehensive review on deep learning based remote sensing image super-resolution methods P. Wang et al. 10.1016/j.earscirev.2022.104110
6. Super-Resolution of Sentinel-2 Images Using Convolutional Neural Networks and Real Ground Truth Data M. Galar et al. 10.3390/rs12182941
7. Single-Image Super-Resolution of Sentinel-2 Low Resolution Bands with Residual Dense Convolutional Neural Networks L. Salgueiro et al. 10.3390/rs13245007
8. Enhanced satellite image resolution with a residual network and correlation filter A. Sharma et al. 10.1016/j.chemolab.2024.105277