zgr6010/HSI_SSFTT
L. Sun, G. Zhao, Y. Zheng, and Z. Wu. "Spectral–Spatial Feature Tokenization Transformer for Hyperspectral Image Classification," in IEEE TGRS, 2022.
This project helps classify different land-cover categories within hyperspectral images. You input raw hyperspectral image data, and it outputs a classification for each pixel, identifying what type of land cover it represents. This is useful for remote sensing analysts, environmental scientists, or urban planners who need to automatically map and understand large areas of terrain.
128 stars. No commits in the last 6 months.
Use this if you need to accurately classify land-cover types from hyperspectral imagery with a method that is both high-performing and computationally efficient.
Not ideal if your primary need is for object detection within standard RGB or multispectral images rather than detailed land-cover classification.
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128
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22
Language
Python
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Last pushed
May 15, 2022
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