Face recognition using fuzzy kernel learning vector quantization
Zuherman Rustam, Rika · Journal of Physics Conference Series · 2018
In recent years, face recognition is widely used in various aspects as a form of technology advancement. Various studies were conducted to improve the accuracy of face recognition. In this research, Learning Vector Quantization and Fuzzy Kernel Learning Vector Quantization were used as a method of classification. The data used in this research was Labeled Face in The Wild-a (LFW-a). This database has no restrictions such as background, expression, position, and so on. Based on test results using LFW-a database, face recognition using LVQ method has highest accuracy at 89,33% and FKLVQ method has highest accuracy at 89,33% as well.