Spatial-Spectral Contrastive Graph Neural Network for Few-Shot Hyperspectral Image Classification

Spatial-Spectral Contrastive Graph Neural Network for Few-Shot Hyperspectral Image Classification

Graph Neural Networks (GNNs) have emerged as a promising solution for few-shot hyperspectral image (HSI) classification. However, existing GNN-based approaches face critical limitations in three key aspects: 1) suboptimal graph topology construction due to fixed or heuristic-based edge definitions,...

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Bibliographic Details
Main Authors: Zhaoxia Xue, Zhiwei Liu, Zhaohui Xue, Tingqiang Song
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Hyperspectral image (HSI)
classification
contrastive learning
graph neural networks (GNNs)
few-shot learning
Online Access:https://ieeexplore.ieee.org/document/11003994/
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