Efficient extraction of spectral-spatial features is essential for accurate hyperspectral image (HSI) classification, where capturing both local texture and global semantic relationships is critical.

Deep learning is transformed by a hybrid model combining text and image processing in a transforming approach to categorization chores. It addresses multi-type data—that which combines text and visual ...