Classification of Sad Emotions and Depression Through Images Using Convolutional Neural Network (CNN)

Authors

  • Muhammad Fathur Prayuda Universitas Trilogi

DOI:

https://doi.org/10.32493/informatika.v6i1.8433

Keywords:

CNN, Depression, Deep Learning

Abstract

The human face has various functions, especially in expressing something. The expression shown has a unique shape so that it can recognize the atmosphere of the feeling that is being felt. The appearance of a feeling is usually caused by emotion. Research on the classification of emotions has been carried out using various methods. For this study, a Convolutional Neural Network (CNN) method was used which serves as a classifier for sad and depressive emotions. The CNN method has the advantage of preprocessing convolution so that it can extract a hidden feature in an image. The dataset used in this study came from the Facial expression dataset image folders (fer2013) where the dataset used for classification was taken with a ratio of 60% training and 40% validation with the results of the trained model of 60% total loss and 68% test accuracy.

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Jurnal Informatika Universitas Pamulang Vol. 6 No. 1 Maret 2021

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Published

2021-03-31

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Vol. 6 No. 1 (2021): JURNAL INFORMATIKA UNIVERSITAS PAMULANG

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