By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

We compare the proposed algorithm with other state-of-the-art graph matching algorithms based on a single-layer structure using synthetic and real data sets and demonstrate the superior performance of ...

This system takes an unstructured text document, and uses an LLM of your choice to extract knowledge in the form of Subject-Predicate-Object (SPO) triplets, and visualizes the relationships as an ...

Compact representation of graph data is a fundamental problem in pattern recognition and machine learning area. Recently, graph neural networks (GNNs) have been widely studied for graph-structured ...