Face pattern recognition using Expectation-Maximization (EM) algorithm
DOI:
https://doi.org/10.12928/bamme.v2i1.5520Keywords:
Data analysis, Expectation-Maximization, Face pattern recognitionAbstract
This paper discuss about the use face patteren recognition which is now days become popular especialy on smartphone lock screen system. The method used in this research are the Expectation – Maximization (EM) Algorithm. EM Algorithm is an iterative optimization method for the estimation of Maximum Likelihood (ML) which is used in incomplete data problems. there are 2 stages, namely the Expectation stage E (E-step) and the Maximization stage M (M-step). These two stages will continue to be carried out until they reach a convergent value. The result of the research shows that EM Algorthm produce high accuracy, it’s about 95% on the data training and 83% accuracy on the data testing.
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