Graph matching remains a core challenge in computer vision, where establishing correspondences between features is crucial for tasks such as object recognition, 3D reconstruction and scene ...

Graph matching and edit distance algorithms form a cornerstone of modern computational techniques used to quantify the similarity between structured data. These methods underpin a wide array of ...

In this presentation, the authors describe the emerging graph pattern approach and the system design of StreamWorks and demonstrate its emerging threat detection capabilities. We are developing ...

We propose a new approach to solve graph isomorphism using parameterized matching. To find isomorphism between two graphs, one graph is linearized, i.e., represented as a graph walk that covers all ...

Abstract: Weighted matching identifies a maximal subset of edges in a graph such that these edges do not share any vertices in common with each other. As a prototypical graph problem, matching has ...

Abstract: Graph matching, as an important query technology, has been widely applied in various fields. With the increasing of graph data, users choose to encrypt a large number of graphs and store ...

In this project, we worked on solving a very real and critical problem: how to allocate hospital resources efficiently during emergencies. When there's a sudden rise in patients, like during a ...

ABSTRACT: Subgraph matching problem is identifying a target subgraph in a graph. Graph neural network (GNN) is an artificial neural network model which is capable of processing general types of graph ...

The research problem focuses on optimizing the University Course Assignment System, where faculty members are categorized into three groups: "x1," "x2," and "x3," each with different course load ...