HyperMODE: A Continuous-Depth Spectral-Spatial Modeling Framework with Mamba and Neural Ordinary Differential Equations for Hyperspectral Image Classification
Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 2026
HyperMODE: A Continuous-Depth Spectral-Spatial Modeling Framework with Mamba and Neural Ordinary Differential Equations for Hyperspectral Image Classification
Published at IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 2026, Volume 19. DOI: 10.1109/JSTARS.2026.3705708.
HyperMODE combines multi-scale spectral-spatial representation learning with Mamba-based spatial propagation and neural ODE feature evolution.
Recommended citation: Tang, Jialin; Lou, Yunduan; Guo, Yanhui; Bai, Yu. (2026). “HyperMODE: A Continuous-Depth Spectral-Spatial Modeling Framework with Mamba and Neural Ordinary Differential Equations for Hyperspectral Image Classification.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 19. doi: 10.1109/JSTARS.2026.3705708.
Recommended citation: Tang, Jialin; Lou, Yunduan; Guo, Yanhui; Bai, Yu. (2026). "HyperMODE: A Continuous-Depth Spectral-Spatial Modeling Framework with Mamba and Neural Ordinary Differential Equations for Hyperspectral Image Classification." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 19. doi: 10.1109/JSTARS.2026.3705708.
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