IEEE

Multiscale Spiking Graph Convolution Aggregation Network for Hyperspectral Image Classification

Abstract: Hyperspectral image (HSI) classification remains challenging due to complex spectral–spatial patterns, the growing demand for energy-efficient modeling in resource-constrained remote sensing ...
Network World

Forescout brings identity-driven segmentation to multi-vendor networks

The new release of Forescout's 4D platform uses a zone modeling approach to group devices, relying on device identity rather than network location. Network segmentation is a foundational security ...
IEEE

Hyperspectral Image Classification via Dynamic Adaptive Graph Convolutional Network

Abstract: Dynamic Graph Convolutional Network (DGCN) can represent temporal evolutionary features. Its compatibility with the spectral-dimensional characteristics of hyperspectral images (HSI), such ...
EurekAlert!

PolyU develops novel AI graph neural network models to unravel interdisciplinary complexities in image recognition and neuroscience

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...