A QA-TSK fuzzy model vs evolutionary decision trees towards nonlinear action pattern recognition
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- @InProceedings{Theodoridis:2010:ICIA,
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author = "Theodoros Theodoridis and Alexandros Agapitos and
Huosheng Hu",
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title = "A QA-TSK fuzzy model vs evolutionary decision trees
towards nonlinear action pattern recognition",
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booktitle = "Proceedings of the 2010 IEEE International Conference
on Information and Automation",
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year = "2010",
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pages = "1813--1818",
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address = "Harbin, China",
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month = jun # " 20-23",
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publisher = "IEEE",
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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",
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DOI = "doi:10.1109/ICINFA.2010.5512225",
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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