Sentence examples for based on two features from inspiring English sources

The phrase "based on two features" is correct and can be used in written English.
For example, "The color of the shirt was based on two features - its material and design."

Exact(10)

An EMG removal algorithm was developed based on two features: Lack of correlation between frequency bands and energy-spread in frequency.

The proposed segmentation works with very little information and is based on two features of the H.264 compressed video: motion vectors associated to the macroblocks and decision modes.

The HUGO nomenclature accounts for KIR protein structure and consists of four major subdivisions based on two features: the number of extracellular Ig domains (2D or 3D) and the length of the cytoplasmic tail (L or S).

However, amongst the hybrid-classifier models based on two features (hybrid:1 6), the best accuracy of 92.14% was achieved by combining the SSC and PSSM pattern information in hybrid-6 classifier, with a sensitivity of 92.64% and specificity of 91.66%.

Since the overall RMSD of the match (0.2 Å) is less than 2 Å, it is evaluated by the SVM, which classifies it as a significant match based on two features: the low RMSD and the similarity between the evolutionary importance of the source template residues and the matched residues (the difference is about 1 percentile rank for each pair of residues).

Leg rubbing was simulated in the grooming model based on two features.

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Similar(50)

In our study, we have developed models based on two feature encoding methods; i) sequence-based and ii) contact-based methods.

By individually training RF classifiers based on two feature sets, we obtained their prediction performance using the same validation strategy.

In this study, we used a special case of an affine transformation including only the translation and scaling based on two feature points.

The strategies are reviewed in detail based on five features, which are the decision variable, objective analysis, constraint, method and tools.

The texture identifier model extracts thirteen features to recognize texture type and the porosity analyzer determines percentage of each type of porosity based on eleven features extracting from the thin section image.

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