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Token Clustering and Semantic Sequence Mamba for Hyperspectral Image Classification
Author1, Author2, Author3, Author4, Author5
hyperspectral imagingtoken clusteringsemantic sequencing
2609.28580
Builder Relevance
1h ago70%
Abstract
This paper proposes STMamba, a method for hyperspectral image classification that organizes sparse tokens into semantically coherent sequences to improve accuracy.
Reality Card
Core Claim
STMamba outperforms state-of-the-art methods in hyperspectral image classification by effectively organizing tokens based on semantic similarity.
Method / Result
STMamba achieved superior performance on three large-scale benchmark datasets.
Limitations
The method's reliance on complex clustering and dynamic selection strategies may hinder reproducibility.
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