Experiments show that our method outperforms comparable methods regarding classiﬁcation accuracy while using a fewer amount of training Fig

CONCLUSION This paper proposes an architecture for HSI classiﬁcation, with spectral partitioning to reduce dimensionality, spatialspectral features extracted by 3D CNN

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Convolution Based Spectral Partitioning Architecture for Hyperspectral Image Classification

cs.CV · 2019-06-27 · unverdicted · novelty 3.0

A 3D CNN with spectral partitioning achieves competitive classification accuracy on the Indian Pines and Salinas hyperspectral datasets.

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Convolution Based Spectral Partitioning Architecture for Hyperspectral Image Classification cs.CV · 2019-06-27 · unverdicted · none · ref 4
A 3D CNN with spectral partitioning achieves competitive classification accuracy on the Indian Pines and Salinas hyperspectral datasets.

Experiments show that our method outperforms comparable methods regarding classiﬁcation accuracy while using a fewer amount of training Fig

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