Tensor-Based Few-Shot Learning for Cross-Domain Hyperspectral Image Classification

Tensor-Based Few-Shot Learning for Cross-Domain Hyperspectral Image Classification

Few-shot learning (FSL) is an effective solution for cross-domain hyperspectral image (HSI) classification, which could address the limited labeled samples of the target domain. Current FSL methods mostly utilize the 3D-CNN to transform the spatial and spectral information into a single feature to m...

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Bibliographic Details
Main Authors: Haojin Tang, Xiaofei Yang, Dong Tang, Yiru Dong, Li Zhang, Weixin Xie
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Remote Sensing
Subjects:
few-shot learning
cross-domain hyperspectral image classification
tensor mathematics
Online Access:https://www.mdpi.com/2072-4292/16/22/4149
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