Lessons from applying SRGAN on Sentinel-2 images for LULC classification

Lessons from applying SRGAN on Sentinel-2 images for LULC classification

Satellite images are commonly used to monitor land use land cover (LULC) changes. Unfortunately, publicly available images often lack the resolution required for detailed urban studies. In this study, we enhanced the resolution of Sentinel-2 (S2) satellite images from 10 meters to 2.5 meters using t...

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Bibliographic Details
Main Authors: Goh, Yun Si, Chua, Wen Qing, Yean, Seanglidet, Lee, Bu-Sung
Other Authors: College of Computing and Data Science
Format: Conference Paper
Language:English
Published: 2024
Subjects:
Computer and Information Science
Classification
Deep learning
Online Access:https://hdl.handle.net/10356/177692

Internet

https://hdl.handle.net/10356/177692

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