It uses multi-block local binary pattern features and the boosting algorithm for face detection [9].
They are represented by multivariate histograms of selected pattern features and their similarity is calculated as the similarity between those histograms.
It first extracts dark areas in full high resolution image, then detects new impact craters within dark areas using a cascade classifier which combines local binary pattern features and Haar-like features trained by an AdaBoost machine learning algorithm.
Note that window size is measured with respect to pattern features and should not depend on interpolation step.
Here we present a new, generic approach for explorative analysis of complex patterning models which focuses on the essential pattern features and their relations to the model parameters.
The wide heterogeneity of the ANA patterns, which need correct interpretation, and the subsequent choice of the most appropriate confirmatory test (ANA subserology), which depend on the pattern feature and on clinical information, hinder any informatics automation, and require the pathologist's intervention.
The meaning of each pattern, the importance of pattern feature and its position, and pattern attractiveness to the C. paucifasciatus remains to be determined and warrant further investigation.
There were delicate patterns featuring ducklings and petals, and then, in the corner, one bright white square with rough stitching that reads: Babies Against the Bomb.
Methodologically, we claim that the XGBoost algorithm used in this study is able to compare cognitively plausible patterns (feature subsets) and highlight the best one, and able to separate categories of participants.
Content based features like lexical patterns, part-of-speech patterns, features corresponding to unigrams and digrams for each representation were used for classification of tweets.
