Joint Classification of Hyperspectral and LiDAR Data Using Multiscale Convolution and Cross-Attention-Guided Mamba (opens in new tab)

With the rapid development of deep learning for hyperspectral image (HSI)–light detection and ranging (LiDAR) land-cover classification, Mamba has shown strong potential in feature representation and generalization. However, insufficient semantic interaction among multimodal features and limited multiscale feature modeling still restrict classification performance. To address these challenges, we propose a novel multiscale convolution and cross-attention-guided Mamba (MCCGM) network for joint...