SpectralMamba: Efficient Mamba for Hyperspectral Image Classification

arXiv:2404.08489v1 Announce Type: new
Abstract: Recurrent neural networks and Transformers have recently dominated most applications in hyperspectral (HS) imaging, owing to their capability to capture long-range dependencies from spectrum sequences. However, despite the success of these sequential architectures, the non-ignorable inefficiency caused by either difficulty in parallelization or computationally prohibitive attention still hinders their practicality, especially for large-scale observation in remote sensing scenarios. To address this issue, we herein propose SpectralMamba -- a novel state space model incorporated efficient deep …

abstract applications architectures arxiv attention capability classification cs.cv dependencies however image imaging mamba networks neural networks parallelization recurrent neural networks spectrum success transformers type