Hyperspectral Image Analysis in Single-Modal and Multimodal setting using Deep Learning Techniques

arXiv:2403.01546v1 Announce Type: cross
Abstract: Hyperspectral imaging provides precise classification for land use and cover due to its exceptional spectral resolution. However, the challenges of high dimensionality and limited spatial resolution hinder its effectiveness. This study addresses these challenges by employing deep learning techniques to efficiently process, extract features, and classify data in an integrated manner. To enhance spatial resolution, we integrate information from complementary modalities such as LiDAR and SAR data through multimodal learning. Moreover, adversarial learning and knowledge …

abstract analysis arxiv challenges classification cs.cv cs.lg deep learning deep learning techniques dimensionality extract hinder image imaging modal multimodal process spatial study type