Abstract
Pattern recognition consists in finding a correspondence between patterns and their prototypes. Intrinsically, it is a distributed process in terms of goals to be reached, zones to be processed and methods to be applied. In this paper, a multi-agent based self-adaptive pattern recognition framework is proposed to cope with the difficulties in the procedure. Each agent is dedicated to recognize a single kind of pattern and communicate with other agents. The cooperation between them reinforces the object-model correspondence hypothesis of each agent and leads to the self-adaptation of their recognition results in order to reach a consistent and integrated interpretation of the whole image. The experiment result validates this approach especially in the flexibility and expansibility of the system.
Highlights
LITERATURE REVIEWThe conventional pattern recognition methods disassociate the recognition procedure into different and isolated stages
This can not fulfill the demand of interpretation of real world and complex images such as Magnetic Resonance Images (MRI) and satellite the use of multiple classifiers and the combination of their classification results is an approach to deal with this problem above
We propose a multi-agent based selfadaptive pattern recognition system to do complex recognition task
Summary
LITERATURE REVIEWThe conventional pattern recognition methods disassociate the recognition procedure into different and isolated stages (preprocess segmentation, feature extraction and pattern classification). The self-adaptive and dynamical changes in recognition model may lead to a better result such as extracting extra features or altering the number of neurons in artificial neuron network in the procedure of pattern recognition when needed. The use of self-adaptation to construct flexible and reliable pattern recognition system adopts two main approaches.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Research Journal of Applied Sciences, Engineering and Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
