AI RESEARCH
SSFT: A Lightweight Spectral-Spatial Fusion Transformer for Generic Hyperspectral Classification
arXiv CS.CV
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ArXi:2604.15828v1 Announce Type: new Hyperspectral imaging enables fine-grained recognition of materials by capturing rich spectral signatures, but learning robust classifiers is challenging due to high dimensionality, spectral redundancy, limited labeled data, and strong domain shifts. Beyond earth observation, labeled HSI data is often scarce and imbalanced, motivating compact models for generic hyperspectral classification across diverse acquisition regimes.