AI RESEARCH
MixerCA: An Efficient and Accurate Model for High-Performance Hyperspectral Image Classification
arXiv CS.CV
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ArXi:2604.26138v1 Announce Type: new Over the past decade, hyperspectral image (HSI) classification has drawn considerable interest due to HSIs' ability to effectively distinguish terrestrial objects by capturing detailed, continuous spectral information. The strong performance of recent deep learning techniques in tasks like image classification and semantic segmentation has led to their growing use in HSI classification, due to their ability to capture complex spatial and spectral features effectively than traditional methods.