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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 ...
IEEE

Multihop Weighted Graph Fusion Network For SAR Image Segmentation

Graph convolutional networks demonstrate advantages such as low sample requirements and strong global information modeling capabilities in the semantic segmentation of synthetic aperture radar (SAR).
GitHub

Open Graph Image Generator

Serverless service that generates dynamic Open Graph images that you can embed in your <meta> tags. For each keystroke, headless chromium is used to render an HTML ...
IEEE

Multigranularity Deep Graph Convolutional Neural Network Node Clustering Leveraging Spatial Information

Abstract: In the era of information explosion, clustering analysis of graph-structured data and empty graph-structured data is of great significance for extracting the intrinsic value of data. From ...