Sentence examples for a matching framework from inspiring English sources

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We propose in this paper an architecture for near-duplicate video detection based on: (i) index and query signature based structures integrating temporal and perceptual visual features and (ii) a matching framework computing the logical inference between index and query documents.

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This paper proposes a theoretical matching framework to analyze firms' and workers' response to a targeted hiring subsidy program when taking into account interactions between segments of the low-skilled labor market.

The procedure is developed following a correlation matching framework, changing the traditional single frequency scan to a spectral scan with a particular shape.

In such situations, numerical models are better suited, using a history matching framework to assist with reservoir and fluid characterization.

Furthermore, we take the scale-sensitive similarities between parts into the evaluation of matching values, and extend the original VSM to a relaxed matching framework.

The proposed algorithm combines a curve matching framework and KF to enhance prediction accuracy of target tracking.

By combining KF with a curve matching framework, we are essentially increasing the number of states upon which the prediction process depends.

13 See Charlot et al. (2005) for a study that investigates the educational decision in a search and matching framework when education is time consuming.

To effectively match them to real fabrics, we introduce a new appearance matching framework to determine their parameters.

In this paper, an optimal model matching framework, where both the feedback and feedforward controllers form the decision variables, is presented which facilitates achieving better performance in terms of the resolution bandwidth and robustness to modeling uncertainties in the closed-loop device.

(Snavely et al. 2006) explored the possibility to create a 3D sparse point cloud from a collection of digital color images (i.e. structure-from-motion). (Furukawa and Ponce 2010) developed a multi-view stereo matching framework, which can generate an accurate, dense, and robust point clouds from stereo color images.

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