the Attention-Based Dual-Branch Complex Feature Fusion Network
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Data Efficient Complex Feature Fusion Network For Hyperspectral Image Classification
arXiv:2606.04710v1 Announce Type: new Abstract: This work presents a data-efficient variant of the Attention-Based Dual-Branch Complex Feature Fusion Network (CFFN) for hyperspectral image classification. The proposed model, termed DE-CFFN, retains the original two-stream structure: the Real-Valued Neural Network (RVNN) processes standard hyperspectral patches, while the Complex-Valued Neural Network (CVNN) handles their Fourier-transformed counterparts.