![]() Experiments using wearable sensing data for multi-class HAR is used, to test the efficacy of the new methodology VFDT+MR, in comparison to a classical data stream mining algorithm VFDT alone. Think about the extreme postures of how a person collapses and free falling from height. For examples, squatting involves actions in between standing and sitting, falling straight down is a sequence of standing, possibly body tiling or curling, bending legs, squatting and crashing down on the floor and there may be totally new (unseen) actions beyond the training instances when it comes to classifying " abnormal " human behaviours. In HAR, most misclassified instances are those belonging to ambiguous movements. Specifically, a new technique namely Misclassified Recall (MR) which is a post-processing step for relearning a new concept, is formulated. You can download in PNG, SVG, AI, EPS, CDR formats. ![]() In this paper, an improved version of Very Fast Decision Tree (VFDT) is proposed which makes use of misclassified results for post-learning. We have 2 free Gamebryo logo png, vector logos, logo templates and icons. ![]() One of the emerging applications of HAR is to monitor needy people such as elders, patients of disabled, or undergoing physical rehabilitation, using sensing technology. ![]() Human activity recognition (HAR) has been a popular research topic, because of its importance in security and healthcare contributing to aging societies.
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