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Masking Hyperspectral Imaging Data with Pretrained Models

The proposed processing pipeline encom- passes two fundamental parts: regions of interest mask generation, followed by the application of hyperspectral data processing techniques solely on the newly masked hyperspectral cube.

Data and Resources

Cite this as

Elias Arbash, Andréa de Lima Ribeiro, Sam Thiele, Nina Gnann, Behnood Rasti, Margret Fuchs, Pedram Ghamisi, Richard Gloaguen (2024). Dataset: Masking Hyperspectral Imaging Data with Pretrained Models. https://doi.org/10.57702/kyjkk3fc

DOI retrieved: December 2, 2024

Additional Info

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Created December 2, 2024
Last update December 2, 2024
Author Elias Arbash
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Andréa de Lima Ribeiro
Sam Thiele
Nina Gnann
Behnood Rasti
Margret Fuchs
Pedram Ghamisi
Richard Gloaguen
Homepage https://github.com/hifexplo/Masking