A heuristic model for optimizing fuzzy knowledge base in a pattern recognition system
Year: 2012
Type: article
Abstract: This study presents a genetic algorithm (GA) to optimize performance of a fuzzy system for reconition of facial expressionfrom images. In proposed model, a Mamdani-type fuzzy rule based system recognizes emotions, and a GA is used to improveaccuracy and robustness of the system. To evaluate system performance, images from FG-Net (FEED) and Cohn-Kanadedatabase were used to obtain the best functions parameters. Proposed model under training process not only increased accuracyrate of emotion recognition but also increased validity of the model in adverse conditions.
Authors: Amir Jamshidnezhad, J. M. Nordin
Institution: National University of Malaysia
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2188169742