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pro vyhledávání: '"Distifano, Salvatore"'
3D Swin Transformer (3D-ST) known for its hierarchical attention and window-based processing, excels in capturing intricate spatial relationships within images. Spatial-spectral Transformer (SST), meanwhile, specializes in modeling long-range depende
Externí odkaz:
http://arxiv.org/abs/2405.01095
Autor:
Ahmad, Muhammad, Distifano, Salvatore, Khan, Adil Mehmood, Mazzara, Manuel, Li, Chenyu, Yao, Jing, Li, Hao, Aryal, Jagannath, Vivone, Gemine, Hong, Danfeng
Hyperspectral Image Classification (HSC) is a challenging task due to the high dimensionality and complex nature of Hyperspectral (HS) data. Traditional Machine Learning approaches while effective, face challenges in real-world data due to varying op
Externí odkaz:
http://arxiv.org/abs/2404.14955
The traditional Transformer model encounters challenges with variable-length input sequences, particularly in Hyperspectral Image Classification (HSIC), leading to efficiency and scalability concerns. To overcome this, we propose a pyramid-based hier
Externí odkaz:
http://arxiv.org/abs/2404.14945
Disjoint sampling is critical for rigorous and unbiased evaluation of state-of-the-art (SOTA) models. When training, validation, and test sets overlap or share data, it introduces a bias that inflates performance metrics and prevents accurate assessm
Externí odkaz:
http://arxiv.org/abs/2404.14944