IEEE

Dual Encoder-Based Dynamic-Channel Graph Convolutional Network With Edge Enhancement for Retinal Vessel Segmentation

Abstract: Retinal vessel segmentation with deep learning technology is a crucial auxiliary method for clinicians to diagnose fundus diseases. However, the deep learning approaches inevitably lose the ...
IEEE

DSR-GCN: Differentiated-Scale Restricted Graph Convolutional Network for Few-Shot Hyperspectral Image Classification

Abstract: Graph convolutional networks (GCNs) have shown great potential for few-shot hyperspectral image (HSI) classification. Mainstream GCNs construct graphs according to single-scale segmentation, ...
GitHub

Superpixel-based Graph Convolutional Network for Semantic Segmentation

@article{jungsuperpixel, title={Superpixel-based Graph Convolutional Network for Semantic Segmentation}, author={Jung, Hoin and Park, Seong Yeon and Yang, Su and Kim, Jin} } Thie repository is an ...
HackerNoon

The Race to Build AI’s Context Layer Is Really About Meaning

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
GitHub

Trustworthy-AI-Group/Adversarial_Examples_Papers

It appears that the List of All Adversarial Example Papers has been experiencing crashes over the past few days. In the absence of this valuable resource, staying up-to-date with the latest research ...