3D-Convolution Guided Spectral-Spatial Transformer for Hyperspectral Image Classification

arXiv:2404.13252v1 Announce Type: cross
Abstract: In recent years, Vision Transformers (ViTs) have shown promising classification performance over Convolutional Neural Networks (CNNs) due to their self-attention mechanism. Many researchers have incorporated ViTs for Hyperspectral Image (HSI) classification. HSIs are characterised by narrow contiguous spectral bands, providing rich spectral data. Although ViTs excel with sequential data, they cannot extract spectral-spatial information like CNNs. Furthermore, to have high classification performance, there should be a strong interaction between the HSI token and the class …

arxiv classification convolution cs.cv cs.lg eess.iv image spatial transformer type