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We propose an autism spectrum disorder (ASD) prediction system based on machine learning techniques. Our work features the novel development and application of machine learning methods over traditional ASD evaluation protocols. Specifically, we are interested in discovering the latent patterns that possibly indicate the symptom of ASD underneath the observations of eye movement. A group of subjects...
Technique for horror video recognition is important for its application in web content filtering and surveillance, especially for preventing children from being threaten. In this paper, a novel horror video recognition algorithm based on fuzzy comprehensive evolution model is proposed. Three low-level video features are extracted as typical features, and they are video key-light, video colour energy...
Advances in video technology are being incorporated into todaypsilas medical research and education. Medical videos contain important medical events, such as diagnostic or therapeutic operations. Automatic discovery and classification of these events are highly desirable and very useful. In this paper, we present a novel method for multi-class educational medical video event categorization. Our method...
In this paper, we propose a generative model-based approach for audio-visual event classification. This approach is based on a new unsupervised learning method using an extended probabilistic latent semantic analysis (pLSA) model. We represent each video clip as a collection of spatial-temporal-audio words, which are generated by fusing the visual and audio features using the pLSA model. Each audio-visual...
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