Face Recognition of Indonesia’s Top Government Officials Using Deep
Convolutional Neural Network

Face Recognition of Indonesia’s Top Government Officials Using Deep
Convolutional Neural Network

deep convolutional neural network; face recognition; facenet; haar cascade classifier

Facial recognition is a part of Computer Vision that is used to get facial coordinates from an image. Many algorithms have
been developed to support Facial Detection such as Cascade Face Detection using Haar-Like features and AdaBoost to classify
its Cascade and Convolutional Neural Network (CNN). Face recognition in this study uses the Deep Convolutional Neural
Network (DCNN) method, and the output of this method is the measurement value of the face. In the model training process,
Triplet Loss from Triplet Network Deep Metric Learning is used to get good face grouping results. The value of this face
measurement will then be measured using the Euclidean distance calculation to determine the similarity of the input face from
the dataset. This Research is using 6 images of Government officers in Indonesia to determine the accuracy of the model when
there is a new picture of these officers inputted into the training machine. The result provides a 94% accuracy level with a
variety of face positions and levels of brightness.

Umar Aditiawarman1
, Dimas Erlangga2
, Teddy Mantoro3
, Lutfil Khakim4

Nusa Putra University

03-02-2023

Fajar bagus W

PDF

Indonesia