Sentence examples for matching algorithms are from inspiring English sources

For evaluation, the proposed symmetry-aware graph matching algorithms are first applied to two datasets involving clear symmetry patterns: a recently proposed architecture image set and a dental panoramic radiograph collection.

As maximum weight matching algorithms are computationally very complex, it is of interest to investigate less complex, but stable algorithms that take into account the variable packet size of data packets.

A wide class of approximate pattern matching algorithms are based on a filtration phase in which spaced seeds are used to discard regions where a match is not likely to occur.

With a polynomial-time complexity O(EVlogE) and actual execution times (in milliseconds, as observed above), we are confident that the proposed maximal matching algorithms are easily scalable for very large real-world networks of several hundreds and even thousands of nodes.

In the matching phase, different matching algorithms are used to calculate the scores for uni-modal and multi-modal biometrics.

Many inexact automatic tree matching algorithms are available.

One useful application of pattern matching algorithms is in the identification of major histocompatibility complex (MHC) ligands and T-cell epitopes.

Detailed information about the three-dimensional reconstruction of the bubble shape, calibration, particle tracking, and stereoscopic vector matching algorithms is presented.

To obtain matched pairs, the kernel matching algorithm is applied using the Epanechnikov kernel.

Elastic matching algorithm is used to perform matching between the two fingerprints.

The proposed SIFT matching algorithm is used as the initial SIFT matching method.