A Spatial-Spectral-Frequency Interactive Network for Multimodal Remote Sensing Classification

ArXi:2510.04628v2 Announce Type: replace Deep learning-based methods have achieved significant success in remote sensing Earth observation data analysis. Numerous feature fusion techniques address multimodal remote sensing image classification by integrating global and local features. However, these techniques often struggle to extract structural and detail features from heterogeneous and redundant multimodal images. With the goal of