IEEE

BAN: A Boundary-Aware Network Based on KAN for Robust Hyperspectral Image Classification Against Adversarial Attacks

Abstract: Deep neural networks (DNNs) have achieved significant advancements in hyperspectral image (HSI) classification, enabling critical applications in environmental monitoring, medical imaging, ...

AI toolkit turns microscopy images into multi-feature microstructure datasets

A research team from The Hong Kong University of Science and Technology (HKUST) has developed GrainBot, an AI-enabled toolkit that automatically extracts and quantifies multiple microstructural ...
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 ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
CNN

With ICE using Medicaid data, hospitals and states are in a bind over warning immigrant patients

The Trump administration’s move to give deportation officials access to Medicaid data is putting hospitals and states in a bind as they weigh whether to alert immigrant patients that their personal ...
IEEE

Hyperspectral Image Classification Based on Subgraph-Dependent Neural Network

Abstract: Hyperspectral image classification methods based on subgraph neural networks (SGNNs) are rarely explored, and its advantage is that it can alleviate the neighbor explosion problem. After ...