Sentence examples for graphs match from inspiring English sources

It is evident from this figure that all three interaction graphs match closely except near the balanced point indicating small partial confinement effects in this case too.

It is evident from this figure that all three interaction graphs match each other closely indicating negligible partial confinement effects in this case too.

It is evident from this figure that the eccentricity-based interaction graphs match each other closely while the full confinement graph is clearly un-conservative indicating a significant partial confinement effects in this case.

It is evident from this figure that all three interaction graphs match each other almost exactly indicating minimal partial confinement effects in this case due to the limited confinement effects in general (wide tie spacing), especially for (α = 45) where small number of corner filaments reaches the ultimate confined strength.

For k=2 the k-clique matching problem reduces to the well-known and extensively studied problem of matching in graphs; a matching in a graph is defined as any subset of nonadjacent edges, which basically are cliques of size 2. In unweighted graphs, matching problems concentrate on finding a maximum matching (a matching with the largest number of edges).

In this paper, we present coarse grained parallel graph algorithms with small message overheads that solve the following standard graph problems related to graph matching: finding maximum matchings in convex bipartite graphs, and finding maximum weight matchings in trees.

One intuitive and conventionally used method is to first segment all image objects, and then use certain matching methods, such as the bipartite graph matching or the constrained graph matching to assign the identities (Long et al., 2008).

Not much effort, however, has been devoted to utilize symmetry information for graph matching.

In this paper we investigate a classical graph matching technique for subgraph isomorphism.

It has proven to be quite effective in exact graph matching.

We present a parallelized bijective graph matching algorithm that leverages seeds and is designed to match very large graphs.