Sentence examples for based on features from from inspiring English sources

Exact(4)

Naturally, all the squares and playing pieces are based on features from Bethesda's role-playing adventure – and houses and hotels are renamed shacks and vaults.

Similarly, another approach, miRdup [ 19], uses Random Forest algorithm integrated with Adaptive Boost (Adaboost) and can be used to detect the positions of miRNAs based on features from five lineages of cleavage sites on the miRNA:miRNA ∗ duplexes.

Our model is based on features from both sequence and structure, thereby incorporation statistics obtained from the entire domain family and domain-specific physical quantities such as surface electrostatics.

To prioritize candidate genes for ciliopathies, a Random Forest classifier was trained to accurately classify positive from negative samples based on features from data generated by our whole-genome siRNA screen, data from centriole formation from Balestra et al., and patterns of gene expression signatures across tissue from the GTEx project (GTEx Consortium, 2013).

Similar(56)

In the decision fusion, two classifiers are used; one based on features extracted from EEG and the other from features obtained from HRV.

In PromoBot, prediction results based on combined features from FDAFSA and RTPFSGA outperformed that based on features extracted from FDAFSA or RTPFSGA alone (Table 5).

Content Based Image Retrieval (CBIR) is an efficient retrieval of relevant images from large databases based on features extracted from the image.

This method could be extremely useful for the identification of domain swap phenomenon from protein structure data based on features derived from protein sequence data and structural co-ordinates.

Furthermore, many applications rely on features derived from specific human poses, such as systems based on features derived from the human face which is only visible when a person is facing the detecting camera.

Most published work in this field is based on features developed from the pixel gray level co-occurrence matrix (GLCM) (13) and from the gray level run length matrix (GLRLM) (14), and on fractal texture methods (9, 15).

This paper presents a new human recognition method based on features extracted from retinal images.

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