A QA-TSK fuzzy model vs evolutionary decision trees towards nonlinear action pattern recognition

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@InProceedings{Theodoridis:2010:ICIA,

• author = "Theodoros Theodoridis and Alexandros Agapitos and Huosheng Hu",
• title = "A QA-TSK fuzzy model vs evolutionary decision trees towards nonlinear action pattern recognition",
• booktitle = "Proceedings of the 2010 IEEE International Conference on Information and Automation",
• year = "2010",
• pages = "1813--1818",
• address = "Harbin, China",
• month = jun # " 20-23",
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, QA-TSK fuzzy model, activity recognition statistics, dimensionality reduction preprocessing, evolutionary decision trees, fuzzy quadruple TSK model, nonlinear action pattern recognition, statistical features, ubiquitous 3D marker based tracker, decision trees, fuzzy set theory, pattern recognition, statistical analysis",
• DOI = "doi:10.1109/ICINFA.2010.5512225",
• abstract = "A comparison among three linear methodologies, a novel auto-adjusted fuzzy quadruple TSK model (QA-TSK) and two evolutionary decision tree representations, is presented. The three architectures make use of a vast number of primitives to reconfigure and evolve their internal structures of the classifier models so that to discriminate among spatial physical activities. Such primitives like statistical features employ a twofold role, initially to model the data set in a dimensionality reduction preprocessing and finally to exploit these attributes to recognise pattern actions. The performance statistics are used for remote surveillance within a smart environment incorporating an ubiquitous 3D marker based tracker which acquires the time series data streams, whereas activity recognition statistics are being generated through an off-line process.",
• notes = "Also known as \cite{5512225}",

}

Genetic Programming entries for Theodoros Theodoridis Alexandros Agapitos Huosheng Hu

Citations