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Yang et al.[29] adopted the AdaBoost algorithm to learn the combination of optimal discriminative features to construct the classifier and classify seven expressions and several AUs.
The challenge task aims to identify and classify seven main Protected Health Information PHII) categories and 25 associated sub-categories.
In the current design, the system can classify seven human postures: falling, standing, sitting, lying, walking, downstairs.
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We then propose a feature set and classify three levels of cognitive load.
We classify three different kinds of possible dynamic behaviors associated with the stable cycles.
Subsequently, the system used a fuzzy logic-based approach to classify six types of defect.
It is possible to classify four kinds of emotions which we described in advance.
The CPG was used to classify two groups.
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