<p class="jove_content">This study presents a two-stage framework for hyperspectral and LiDAR land-cover classification using MetaFormer feature extraction and bidirectional flow matching for cross-modal alignment before fusion. Evaluation on three public benchmark datasets demonstrates competitive classification performance under fixed benchmark protocols.</p>

continuous-cross-modal-vector-field-learning-for-hyperspectral-lidar

Institution - Shaanxi A&F Technology University

Articles Published in JoVE