Sentence examples for features alignment from inspiring English sources

A novel video similarity measure is proposed by using visual features, alignment distances and speech transcripts.

It combined several gene pairwise features (alignment-based and synteny measures with others derived from the pairwise comparison of the physicochemical properties of amino acids) to address Big Data problems.

Considering all these previous remarks about OD, we propose a new supervised approach for pairwise OD (POD) that combines several gene pairwise features (alignment-based and synteny measures with others derived from the pairwise comparison of the physicochemical properties of amino acids) to address big data problems [ 30].

This observation motivates us to propose a Spectral Feature Alignment (SFA) based method to align workflow DS templates from different domains in a latent space by modeling the correlation between the DI and DS workflow templates in a bipartite graph and using DS features as a bridge for cross-domain Big Data classification.

Ridge-colour matching is introduced as a criterion for edge flipping to improve feature alignment.

An pre-alignment of fingerprints is assumed which is rarely the case in practice (feature alignment represents a fundamental step in conventional fingerprint recognition systems).

Obviously, the development of multi-biometric cryptosystems is accompanied by further issues such as common data representation, storage requirement, or feature alignment [22].

We propose Spectral Feature Alignment (SFA) [32] based algorithm to find a new representation for cross-domain process data, such that the gap between domains can be reduced.

Fig. 1 Survivor MEA summary and design feature alignment (adapted from http://wordpress.unlvcoe.net/wordpress/wp-content/uploads/2013/01/Survivor-MEA-Teacher-Materials.pdf).pdf

Compared to the previous harmonic volumetric mapping computation using MFS, this new scheme is more efficient and accurate, and can support feature alignment and adaptive refinement.

The work by Pan [83] proposes a spectral feature alignment (SFA) transfer learning algorithm that discovers a new feature representation for the source and target domain to resolve the marginal distribution differences.