Sentence examples similar to the graph model built from inspiring English sources

The correlation network is a graph model built of edges and nodes, where nodes represent gene probes and a set of sample expression levels for that gene, and an edge represents the level of correlation the two expression vectors.

Thus, in this paper, we propose a novel scene text detection approach using graph model built upon Maximally Stable Extremal Regions (MSERs) to incorporate various information sources into one framework.

Note that, b 2 is also a prey of b 1. Figure 2- b) is the bipartite graph model we built from the original graph.

This paper presents a domain specific visual language developed expressly for the evolution of domain-specific visual languages, and uses concepts from graph-rewriting to specify and carry out the transformation of the models built using the original DSVL.

Graphs showing ROC curves for the three data sets using the best classification models built using circular fingerprint bond depths ranging from 4-6.

All the models built were evaluated qualitatively.

Where users are focused, the graph gets built out.

In this paper, firstly, due to lots of graphs (models) are built on the basis of various simple and small elements (components), we provide primarily some helpful network-operation, such as link-operation and merge-operation, to generate more realistic and complicated graphs (models).

The graphs were built using R3.0.2.

Graphs showing classification performance for the three data sets in terms of MCC against subsample length q for models built using circular fingerprint bond depths ranging from 4-6.

Specifically, MRI based connectomics is an emerging approach to extract information from MRI data that exhaustively maps inter-regional connectivity within the brain to build a graph model of its neural circuitry known as brain network.