3D‐TabNetHS: A hyperspectral image classification method based on improved interpretable 3D attentive TabNet

3D‐TabNetHS: A hyperspectral image classification method based on improved interpretable 3D attentive TabNet

Abstract The classification methods for hyperspectral images (HSI) based on decision trees and convolutional neural networks have shown increasing advantages, but these methods often require a large number of labelled samples for learning, which is difficult for HSI, and the interpretability of the...

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Bibliographic Details
Main Authors: Ning Li, Daozhi Wei, Shucai Huang, Yong Zhang
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:IET Radar, Sonar & Navigation
Subjects:
computer vision
convolutional neural nets
feature extraction
feature selection
image classification
spectral analysis
Online Access:https://doi.org/10.1049/rsn2.12678

Internet

https://doi.org/10.1049/rsn2.12678

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