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All Journal Jurnal Nasional Teknologi Informasi dan Aplikasinya
Esa Sulistyo Aji Nugroho
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Computer Science & IT Engineering

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Custom Convolutional Neural Network (CNN) Model untuk Pengenalan Emosi pada Real-Time Video Esa Sulistyo Aji Nugroho; I Wayan Santiyasa
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 3 No. 3 (2025): JNATIA Vol. 3, No. 3, Mei 2025
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2025.v03.i03.p15

Abstract

Facial Expressions Recognition (FER) is a vital task in human-computer interaction. This field can be used to augment many other fields such as learning, content suggestions and many more. This paper aims to propose a simple FER approach utilizing a custom Convolutional Neural Network (CNN) architecture for real-time emotion recognition, complemented by Hard Cascades for efficient face detection. The model is trained on a large and reputable dataset encompassing various facial expressions classified into 7 main emotions. The result of this study yields an accuracy of 60.78% achieved on the training data and 57.32% on the validation data. This shows that with even a very simplified approach with a custom CNN model, we can relatively accurately recognize facial expressions. This study aims to be a kind of groundwork for more advanced approaches to FER. 
Co-Authors I WAYAN SANTIYASA