Deformable Transformer and Spectral U-Net for Large-Scale Hyperspectral Image Semantic Segmentation

Deformable Transformer and Spectral U-Net for Large-Scale Hyperspectral Image Semantic Segmentation

Remote sensing semantic segmentation tasks aim to automatically extract land cover types by accurately classifying each pixel. However, large-scale hyperspectral remote sensing images possess rich spectral information, complex and diverse spatial distributions, significant scale variations, and a wi...

Täydet tiedot

Bibliografiset tiedot
Päätekijät: Tianjian Zhang, Zhaohui Xue, Hongjun Su
Aineistotyyppi: Artikkeli
Kieli:English
Julkaistu: IEEE 2024-01-01
Sarja:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Aiheet:
Deep learning
hyperspectral remote sensing
large-scale
semantic segmentation
transformer
Linkit:https://ieeexplore.ieee.org/document/10729869/

Internet

https://ieeexplore.ieee.org/document/10729869/

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