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All Journal CCIT (Creative Communication and Innovative Technology) Journal
Naufal Alwan Hafidhi
Universitas Raharja
Computer Science & IT

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Deep Learning on Facial Expression Detection : Artificial Neural Network Model Implementation Hendra Kusumah; Muhammad Suzaki Zahran; Paksi Ryandana Cholied; Muhammad Surya Alkusna; Naufal Alwan Hafidhi
CCIT Journal Vol 16 No 1 (2023): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (939.203 KB) | DOI: 10.33050/ccit.v16i1.2518

Abstract

The moods, emotions, and even medical issues of a person can frequently be seen directly reflected in their facial expressions. The fields of social science and human-computer interaction have recently begun to pay more attention to facial emotion detection as a result of this. The primary focus of this study is on the automatic recognition of human facial expressions using an artificial neural network (ANN) model and a technique based on straightforward convolution. The dataset utilized is a self-mined dataset that was obtained by utilizing the web scraping approach on Google Image with the help of the Selenium package for Python. A dataset containing six categories of fundamental human expressions that are likely to be met on a daily basis, namely anger, confusion, contempt, crying, sadness, disgust, and happiness, with a total of 6,016 photos being used. The goal of this research is to determine how accurate the model of artificial neural networks can be in predicting.
Co-Authors Hendra Kusumah Muhammad Surya Alkusna Muhammad Suzaki Zahran Paksi Ryandana Cholied