Research Repository

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

Theodoridis, Theodoros and Agapitos, Alexandros and Hu, Huosheng (2010) A QA-TSK fuzzy model vs evolutionary decision trees towards nonlinear action pattern recognition. In: 2010 International Conference on Information and Automation (ICIA), 2010-06-20 - 2010-06-23.

Full text not available from this repository.

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 in this paper. The three architectures make use of a vast number of primitives1 utilised 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 being utilised for remote surveillance within a smart environment incorporating an ubiquitous 3D marker based tracker which acquires the timeseries data streams, whereas activity recognition statistics are being generated through an off-line process. ©2010 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: 2010 IEEE International Conference on Information and Automation, ICIA 2010
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 17 Dec 2014 11:33
Last Modified: 15 Jan 2022 00:45
URI: http://repository.essex.ac.uk/id/eprint/9086

Actions (login required)

View Item View Item