DotWang/SSGRN
[TNNLS 2023] The official repo for the paper "Spectral-Spatial Global Graph Reasoning for Hyperspectral Image Classification".
This tool helps remote sensing specialists and geoscientists classify different land cover types in hyperspectral satellite or aerial images. You input raw hyperspectral images, and it outputs a classification map, clearly labeling areas like specific crops, water bodies, or urban developments. This is designed for researchers and analysts working with detailed spectral data to understand environmental or agricultural landscapes.
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Use this if you need to accurately identify and map different materials or land cover types from hyperspectral imagery, generating clear classification maps for your analysis.
Not ideal if you're looking for a user-friendly, out-of-the-box software with a graphical interface for general image classification tasks.
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Python
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Last pushed
Oct 13, 2024
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