Abstract: Convolutional neural networks (CNNs) have been widely applied to hyperspectral image classification (HSIC). However, traditional convolutions can not effectively extract features for objects ...
Abstract: Hyperspectral imaging (HSI) plays a pivotal role across diverse sectors—including agriculture, environmental monitoring, and defense—by capturing rich spectral information that enables ...
This paper describes a simple variant of the spectral clustering algorithm based on embedding the vertices of the graph in log(k) dimensions, rather than the usual k dimensions. Furthermore, this ...
This project focuses on enhancing EEG-based emotion classification (valence/arousal) using graph signal processing and advanced Graph Neural Networks (GNNs). It combines PLV-based brain connectivity, ...
Understanding diffraction and dispersion is key to optical science, influencing technologies like spectroscopy, fiber optics, ...
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