Sentence examples for models for detecting from inspiring English sources

This paper has studied the characteristics of the additive interference models for detecting RFID reader-to-reader collisions.

This paper investigates the characteristics of the additive interference models for detecting RFID reader-to-reader collisions.

Using linguistic analysis methods, this paper aims to build computational models for detecting stigma expressions in Chinese social media posts (Sina Weibo).

These features deal with the underlying meaning or concepts of the words and are used by Raymond et al. [1] to create semantic language models for detecting untruthful reviews.

As mentioned above, many studies have proposed various probability models for detecting DMCs [ 13- 15].

Site-specific models for detecting positive selection work best when detecting pervasive selection pressures.

This library was used to analyze the spectra of sample extracts and create mathematical models for detected metabolites in a cumulative manner.

In this study we compared three models namely M0, can be called as one ratio model where all branches have equal rate (dN/dS = constant value), M2 (null model) was used to detect null hypothesis and M2a (alternate model) model used for detecting positive selection or acceleration in the post duplication branch forming the novel subfamilies of GGT and third model [ 53– 53].

We propose a stereo contrast model for detecting stereo saliency.

We propose a stereo focus model for detecting stereo saliency.

Golsefid et al. [59] proposed a fuzzy clustering model for detecting overlapping communities in complex networks.