Graph-Based Radiomics Feature Extraction From 2D Retina Images ... a local fragment of $35\times 35$ pixels is extracted and used as input to the classification model. A Convolutional Neural Network ...

Molecular representation learning has attracted much attention recently. A molecule can be viewed as a 2D graph with nodes/atoms connected by edges/bonds, and can also be represented by a 3D ...

Research team led by Chuliang Weng introduces D2-GCN, a groundbreaking disentangled graph convolutional network that dynamically adjusts feature channels for enhanced node representation ...

Illustration of the comparative analysis between graph filtration and Vietoris-Rips filtration for both dimension-0 (H0) and dimension-1 (H1) in the classification of (A) healthy controls (HC) vs.

Existing few-shot image classification networks aim to perform prediction on images belonging to classes that were not seen during training, with only a few labeled images, which are randomly picked ...