In this paper, we tackle the problem of localizing graphical symbols on complex technical document images by using an original approach to solve the subgraph isomorphism problem. In the proposed ...

Graph algorithms are integral for solving complex programming challenges. They provide methods for handling data relationships through graphs, which are essential in fields like network analysis, ...

United States County Adjacency Data, Corrected. Contribute to turibe/us-county-adjacency development by creating an account on GitHub.

In this letter, we propose a visibility graph (VG)-based adjacency matrix representation of LS in conjunction with a residual deep neural network (ResNet) for accurate detection of COPD, namely, the ...

Many algorithms for analyzing parallel programs, for example to detect deadlocks or data races or to calculate the execution cost, are based on a model variously known as a cost graph, computation ...

On top of these graph structures, graph rewriting techniques provide another powerful layer of technology. By enabling the formal definition of rules for transforming graph structures, they allow on ...

Knowledge graphs are well-suited to organizations with large data sets and where extracting knowledge often proves burdensome.