Nature

Spatial-spectral graph convolutional network for automatic pigment mapping of historical artifacts

Hyperspectral image classification is a challenging task due to the lack of ground-truth labels and high dimensionality of spectral bands. For hyperspectral image (HSI) data of cultural heritage ...
Nature

A graph convolutional network with dynamic weight fusion of multi-scale local features for diabetic retinopathy grading

Diabetic retinopathy (DR) is a serious ocular complication that can pose a serious risk to a patient’s vision and overall health. Currently, the automatic grading of DR is mainly using deep learning ...
AlphaGalileo

AdapGNN: A New Framework Enhances Explainability of Graph Neural Networks for Molecular Property Prediction

Researchers have developed AdapGNN, a novel model-agnostic framework that addresses the oversmoothing problem in graph neural ...
Tech Xplore on MSN

AI model predicts robberies across US cities with 86.3% accuracy

Researchers have developed an artificial intelligence model that predicts crime more accurately than several existing ...