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Jul 7, 2021 · Abstract:Hyperspectral (HS) images are characterized by approximately contiguous spectral information, enabling the fine identification of ...
Spectralformer: Rethinking hyperspectral image classification with transformers, IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2022, vol. 60, pp. 1 ...
Feb 8, 2024 · We evaluate the classification performance of the proposed SpectralFormer on three HS datasets by conducting extensive experiments, showing the ...
This work rethink HS image classification from a sequential perspective with transformers and proposes a novel backbone network called SpectralFormer, ...
Abstract—Hyperspectral (HS) images are characterized by approximately contiguous spectral information, enabling the fine identification of materials by ...
Feb 21, 2022 · We evaluate the classification performance of the proposed SpectralFormer on three HS datasets by conducting extensive experiments, show- ing ...
Therefore, to enhance model's performance and practicality, we propose an efficient transformer backbone for HSI classification, named Efficient-Spectralformer.
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SZU-AdvTech-2022/037-SpectralFormer-Rethinking-Hyperspectral-Image-Classification-with-Transformers · Folders and files · Latest commit · History · About · Releases.
May 23, 2024 · SpectralFormer: Rethinking Hyperspectral Image Classification With Transformers. D. Hong, Zhu Han, Jing Yao, Lianru Gao, Bing Zhang, A. Plaza ...
Read Wonders: A novel backbone network called SpectralFormer is proposed, capable of learning spectrally local sequence information from neighboring bands ...