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Special issue : Computational intelligence models for image processing and information reasoning

Lim, Chee Peng, Abeynayake, Canicious, Sato-Ilic, Mika and Jain, Lakhmi C. 2013, Special issue : Computational intelligence models for image processing and information reasoning, Journal of intelligent and fuzzy systems, vol. 24, no. 2, pp. 199-200.

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Title Special issue : Computational intelligence models for image processing and information reasoning
Author(s) Lim, Chee Peng
Abeynayake, Canicious
Sato-Ilic, Mika
Jain, Lakhmi C.
Journal name Journal of intelligent and fuzzy systems
Volume number 24
Issue number 2
Start page 199
End page 200
Total pages 2
Publisher IOS Press
Place of publication Amsterdam, The Netherlands
Publication date 2013
ISSN 1064-1246
1875-8967
Keyword(s) Bayesian Belief Network
computational Intelligence
fuzzy models
image processing
information reasoning
membrane computing
Summary Computational Intelligence (CI) models comprise robust computing methodologies with a high level of machine learning quotient. CI models, in general, are useful for designing computerized intelligent systems/machines that possess useful characteristics mimicking human behaviors and capabilities in solving complex tasks, e.g., learning, adaptation, and evolution. Examples of some popular CI models include fuzzy systems, artificial neural networks, evolutionary algorithms, multi-agent systems, decision trees, rough set theory, knowledge-based systems, and hybrid of these models. This special issue highlights how different computational intelligence models, coupled with other complementary techniques, can be used to handle problems encountered in image processing and information reasoning.
Language eng
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C4 Letter or note
Persistent URL http://hdl.handle.net/10536/DRO/DU:30055292

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
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