IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
Vol 16, No 2 (2022): April

Face Expression Classification in Children Using CNN

Yusril Ihza (Master Program of Computer Science, FMIPA UGM, Yogyakarta)
Danang Lelono (Department of Computer Science and Electronics, FMIPA UGM, Yogyakarta)



Article Info

Publish Date
30 Apr 2022

Abstract

One of the turbulent emotions can be recognized from facial expressions. When compared with adults, children's facial expressions are more expressive for positive emotions and ambiguous for negative emotions so that they are much more difficult to recognize. Ambiguous in terms of negative emotions, for example, when children are angry, sometimes they show an expressionless face, making it difficult to know what emotions the child is experiencing. Therefore, it is proposed research using Convolutional Neural Network with ResNet-50 architecture. According to [1] CNN Resnet-50 is superior to other facial recognition methods, specifically in the classification of facial expressions. CNN ResNet-50 generates a model during the training process, and the model will be used during the testing process. The dataset used is Children's Spontaneous facial Expressions (LIRIS-CSE) data proposed by [2]. CNN ResNet-50 can identify children's expressions well, including expressions of anger, disgust, fear, happy, sad and surprise. The results showed a very significant increase in accuracy, namely in testing data testing reached 99.89%.

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Journal Info

Abbrev

ijccs

Publisher

Subject

Computer Science & IT Control & Systems Engineering

Description

Indonesian Journal of Computing and Cybernetics Systems (IJCCS), a two times annually provides a forum for the full range of scholarly study . IJCCS focuses on advanced computational intelligence, including the synergetic integration of neural networks, fuzzy logic and eveolutionary computation, so ...