Hypergraph Convolutional Subspace Clustering With Multihop Aggregation for Hyperspectral Image

Subspace clustering methods have become a powerful tool to cluster hyperspectral imaging (HSI) data as they ensure theoretical guarantees and empirical success. However, existing methods explore subspace representation in the Euclidean space, and thus, failing to exploit the high-order relationship...

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Detalhes bibliográficos

Principais autores:	Zijia Zhang, Yaoming Cai, Wenyin Gong, Pedram Ghamisi, Xiaobo Liu, Richard Gloaguen
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2022-01-01
coleção:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Assuntos:	Graph representation learning hypergraph convolutional networks (HGCN) hyperspectral image clustering subspace clustering
Acesso em linha:	https://ieeexplore.ieee.org/document/9657490/
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