Open AccessOptimization of The Backpropagation Method with Nguyen-widrow in Face Image Classification
Author(s) -
Ichsanuddin Hakim,
Syahril Efendi,
Pahala Sirait
Publication year - 2021
Publication title -
randwick international of social science journal/randwick international of social science journal
Language(s) - English
Resource type - Journals
eISSN - 2722-5674
pISSN - 2722-5666
DOI - 10.47175/rissj.v2i2.226
Subject(s) - backpropagation , initialization , computer science , artificial intelligence , face (sociological concept) , process (computing) , artificial neural network , pattern recognition (psychology) , computer vision , social science , sociology , programming language , operating system
In this study, it is proven that the Nguyen-widrow algorithm can optimize the Backpropagation method in terms of initializing weights and bias. With the Nguyen-widrow algorithm, the Backpropagation method can recognize facial images faster with better accuracy. In the testing process with hidden layer 6 neurons, at a target error of 0.01, the standard Backpropagation method obtained an accuracy of 96%, while the optimization Backpropagation method obtained a higher accuracy of 98%. So on with hidden layers 7, 8, 9, and 10 neurons. then in other words this research can be used to advance human technology in facilitating all aspects of life with these algorithms and methods. With the accuracy and speed of capturing facial images, this can be used as policy like a surveillance camera, traffic protection, and many other things that can be used in social life.