Combination Of Haar Cascade Classifier And Convolutional Neural Networks For Classification Of Face Image

Tarigan, Irwa Jani

International Journal of Information System and Innovative Technology
Vol. 1 No. 2 (2022): December

Humans are able to carry out face recognition in everyday of life, where faces are a unique identity, are a complex problem in machine learning. Face recognition technology is also very useful in various fields today, such as access control, attendance and security systems. This study aims to obtain a level of accuracy in classifying image data with a combination of algorithm haar-like feature with convolutional neural network, where haar-like feature is used to detect faces in image data, while convolutional neural network is used for face recognition. Image data using in this study, Japanes Female Facial Expression (JAFFE), the experimental results give the best accuracy results at the 500 epoch of 95.14% and a running time of 1.52 seconds.