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Traditional to Transformers: A Survey on Current Trends and Future Prospects for Hyperspectral Image Classification
April 24, 2024, 4:45 a.m. | Muhammad Ahmad, Salvatore Distifano, Manuel Mazzara, Adil Mehmood Khan
cs.CV updates on arXiv.org arxiv.org
Abstract: Hyperspectral image classification is a challenging task due to the high dimensionality and complex nature of hyperspectral data. In recent years, deep learning techniques have emerged as powerful tools for addressing these challenges. This survey provides a comprehensive overview of the current trends and future prospects in hyperspectral image classification, focusing on the advancements from deep learning models to the emerging use of transformers. We review the key concepts, methodologies, and state-of-the-art approaches in deep …
abstract arxiv challenges classification cs.cv current data deep learning deep learning techniques dimensionality future image nature overview prospects survey tools transformers trends type
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