SUPER-RESOLUTION OF MULTISPECTRAL SATELLITE IMAGES USING CONVOLUTIONAL NEURAL NETWORKS

31 citations as recorded by crossref.

1. Generative adversarial approach to urban areas NDVI estimation: A case study of Łódź, Poland M. Adamiak et al. https://doi.org/10.14746/quageo-2023-0007
2. Investigating the impact of spectral band upsampling on Sentinel-2 multispectral image classification T. Dündar https://doi.org/10.51489/tuzal.1729306
3. Parametric regularization loss in super-resolution reconstruction S. Viriyavisuthisakul et al. https://doi.org/10.1007/s00138-022-01315-9
4. Applications of deep learning-based denoising methodologies for scanning electron microscope images S. Shin et al. https://doi.org/10.1088/1361-6501/ad7e41
5. Super-resolving satellite imagery through in-depth analysis of GAN models N. Shamsudin et al. https://doi.org/10.1016/j.procs.2026.06.307
6. Deep learning generated observations of galaxy clusters from dark-matter-only simulations A. Caro et al. https://doi.org/10.1093/rasti/rzaf007
7. Advancing image super-resolution techniques in remote sensing: A comprehensive survey Y. Qi et al. https://doi.org/10.1016/j.isprsjprs.2025.10.024
8. Drone-Enabled Multimodal Platform for Inspection of Industrial Components P. Nooralishahi et al. https://doi.org/10.1109/ACCESS.2022.3167393
9. Enhancing interpretability in generative modeling: statistically disentangled latent spaces guided by generative factors in scientific datasets A. Ganguli et al. https://doi.org/10.1007/s10994-025-06816-y
10. Investigation into Perceptual-Aware Optimization for Single-Image Super-Resolution in Embedded Systems K. Vu et al. https://doi.org/10.3390/electronics12112544
11. Revisiting Cosa (Ansedonia, Italy): contributions of SAR-X images from the PAZ satellite to non-invasive archaeological prospecting J. Fiz Fernández et al. https://doi.org/10.4995/var.2024.21135
12. Satellite Image Super-Resolution by 2D RRDB and Edge-Enhanced Generative Adversarial Network T. Liu & Y. Chen https://doi.org/10.3390/app122312311
13. Band Reconstruction Using a Modified UNet for Sentinel-2 Images I. Neagoe et al. https://doi.org/10.1109/JSTARS.2023.3276912
14. IV-PSNR—The Objective Quality Metric for Immersive Video Applications A. Dziembowski et al. https://doi.org/10.1109/TCSVT.2022.3179575
15. Nighttime Ground Radar-Like Rainfall Estimation Using Virtual Visible and Near-Infrared and Real Infrared Bands of Advanced Meteorological Imager Y. Kim et al. https://doi.org/10.1109/TGRS.2025.3559686
16. Enhancing hyperspectral image compression using learning-based super-resolution technique M. Ouahioune et al. https://doi.org/10.1007/s12145-021-00623-4
17. Semantic-Aware Image Matching for Large-Scale 3-D Reconstruction of the Martian Surface From Rover Images Z. Li & B. Wu https://doi.org/10.1109/TGRS.2025.3594413
18. High-resolution processing of Himawari meteorological satellite data N. KOISO et al. https://doi.org/10.2480/agrmet.D-24-00031
19. Downscaling atmospheric chemistry simulations with physically consistent deep learning A. Geiss et al. https://doi.org/10.5194/gmd-15-6677-2022
20. GSR-SWIR: SWIR band for Resourcesat LISS-4 from LISS-3 using guided super-resolution L. James et al. https://doi.org/10.1080/2150704X.2025.2522937
21. A deep learning based classification of atmospheric circulation types over Europe: projection of future changes in a CMIP6 large ensemble M. Mittermeier et al. https://doi.org/10.1088/1748-9326/ac8068
22. DefaceQA - automated quality assessment of brain MRI defacing software M. Khodaei Dolouei et al. https://doi.org/10.1186/s12880-026-02207-4
23. Evaluating the impact of super-resolution on land use and land cover classification using sentinel-2 imagery F. Şi̇mşek & K. Kalkan https://doi.org/10.1007/s11042-026-21754-0
24. Mapping invasive alien plant species with very high spatial resolution and multi-date satellite imagery using object-based and machine learning techniques: A comparative study F. Nininahazwe et al. https://doi.org/10.1080/15481603.2023.2190203
25. Impact of Thailand’s Eastern Economic Corridor (EEC) Policy on Land Use: Prediction Up to 2040 by Combining CNN Land Cover and Machine Learning Methods on Socio-Economic Data D. Gomez et al. https://doi.org/10.1007/s12061-025-09672-4
26. Denoising of pre-beamformed photoacoustic data using generative adversarial networks A. Refaee et al. https://doi.org/10.1364/BOE.431997
27. A Tripartite Data-Driven Approach for Wide-Band Electromagnetic Imaging A. Al-Saffar et al. https://doi.org/10.1109/TCI.2021.3126928
28. Land cover classification through Convolutional Neur-al Network model assembly: A case study of a local rural area in Thailand D. Fitton et al. https://doi.org/10.1016/j.rsase.2022.100740
29. Quantitative detection of corrosion minerals in carbon steel using shortwave infrared hyperspectral imaging T. De Kerf et al. https://doi.org/10.1039/D2RA05267A
30. A Method to Downscale MODIS Surface Reflectance Using Convolutional Neural Networks Y. Zhang & Z. Xiao https://doi.org/10.3390/rs15082102
31. QMRNet: Quality Metric Regression for EO Image Quality Assessment and Super-Resolution D. Berga et al. https://doi.org/10.3390/rs15092451