Academic
Keywords
Activity Recognition

,Activity Recognition,Active Recognition,activities recognition,activation Recognition

Activity Recognition
Publications: 1,255| Citation Count: 8,210
Stemming Variations: Active Recognition, activities recognition, activation Recognition
Cumulative Annual
    • Activity recognition is a hot topic in context-aware computing. In activity recognition, machine learning techniques have been widely applied to learn the activity models from labeled activity samples. Since labeling samples requires human's efforts, most existing research in activity recognition focus on refining learning techniques to utilize the costly labeled samples as effectively as possible. However, few of them consider using the costless unlabeled samples to boost learning performance...

    Donghai Guanet al. Activity Recognition Based on Semi-supervised Learning

    • Activity recognition is a process by which the ongoing observed behavior of an agent is tracked and mapped to a given model, explaining the behavior and accounting for hidden or unobservable state (e.g., goals or beliefs of the observed agents). Various methods for activity recognition exist...

    Einat Marhasevet al. Non-stationary Hidden Semi Markov Models in Activity Recognition

    • Activity recognition is an important topic in ubiquitous computing. In activity recognition, supervised learning techniques have been widely applied to learn the activity models...

    Donghai Guanet al. Activity recognition with the aid of unlabeled samples

    • Activity Recognition is an emerging field of research, born from the larger fields of ubiquitous computing, context-aware computing and multimedia. Recently, recognizing everyday life activities becomes one of the challenges for pervasive computing...

    Pierluigi Casaleet al. Human Activity Recognition from Accelerometer Data Using a Wearable De...

    • Activity recognition is an important application of body sensor networks. To this end, accurate segmentation of different episodes in the data stream is a pre-requisite of subsequent pattern classification. Current techniques for this purpose tend to require specific supervised learning, thus limiting their general application to pervasive sensing applications...

    Aziah Aliet al. Episode Segmentation Using Recursive Multiple Eigenspaces

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