Sentence examples for features into two from inspiring English sources

Based on the feature properties, we clustered the visual features into two main groups, namely shape and texture cluster groups.

Usually, the SVM classifier is used for classification of features into two classes.

The paleontologists divided the fossils, based on skeletal and tooth features, into two evolutionary groups, one southern and the other northern.

In this paper, we study this problem explicitly by dividing the local features into two groups to reflect the relative contrast between the local and global intensities.

In this work, we propose a new concave-convex partition (CCP) strategy to improve LBP and LTP by dividing local features into two distinct groups, i.e., concave and convex, according to the contrast between local and global intensities.

Based on the analysis of the limitation of traditional LBP-based methods, CCP is presented to group local features into two categories in order to reflect the contrast between local and the global intensities.

These are further classified, on the basis of additional motif features, into three subfamilies: CHD1-2 (class I), CHD3-5 (Class II) and CHD 6-9 (class III)25,28.

In the second phase, the fuzzy c-means (FCM) is used to group features into three clusters: the shot change (SC) cluster, the suspected shot change (SSC) cluster, and the no shot change (NSC) cluster.

We classify image features into four categories: shape, appearance, motion, and depth features.

The performance of the algorithms are evaluated using 10-fold cross validation method.The crossvalidation method divides the extracted features into ten equal sets.

For comparison purpose, we subdivided the 95 features into four sets, i.e., D13 (13 diagnostic features), T82 (82 textural features), A95 (the combination of all 95 features), and S6 (6 selected features from A95).