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, doi: 10.3233/IFS-2012-0546.
Attached Files
Name
Description
MIMEType
Size
Downloads
Title
Special issue : Computational intelligence models for image processing and information reasoning
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.
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.
Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO.
If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.
Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.