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Recognition of human actions by using wearable sensors has become an important research field. Segmentation to sensor data is a vital issue in reconstructing and understanding human daily actions, and strongly affects the accuracy of human actions recognition. Traditional online segmentation approaches are mostly designed for one-dimensional sensor data, which greatly limits these approaches to multi-dimensional...
This work applies a variety of multilinear function factorisation techniques to extract appropriate features or attributes from high dimensional multivariate time series for classification. Recently, a great deal of work has centred around designing time series classifiers using more and more complex feature extraction and machine learning schemes. This paper argues that complex learners and domain...
Sign language data can be expressed as the positional changes of hands over time. Although increasing the number of hand movement sensors increases the recognition rate, the data scales become larger. In addition, each sign language data has a different duration. When large data are generated continuously, lower memory usage and a standardized form of data are necessary to be applied immediately in...
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