USK-FEMO: A Face Emotion Dataset using Deep Learning for Effective Learning-Reference-Cited by-同舟云学术

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USK-FEMO: A Face Emotion Dataset using Deep Learning for Effective Learning

Published:2023-08-02 Issue: Volume: Page:
ISSN:
Container-title:2023 2nd International Conference on Computer System, Information Technology, and Electrical Engineering (COSITE)
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Author:

Muhajir Muhajir¹,Oktiana Maulisa¹,Muchtar Kahlil¹,Fitria Maya¹,Akhyar Akhyar²,Pratama Muhammad Dandy¹,Lin Chih-Yang³

Affiliation:

1. Universitas Syiah Kuala,Department of Electrical and Computer Engineering,Banda Aceh,Indonesia

2. Universiti Kebangsaan Malaysia,Faculty of Engineering and Built Environment,Department of Electrical, Electronic and Systems Engineering,Selangor,Malaysia

3. National Central University,Department of Mechanical Engineering,Taoyuan City,Taiwan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10249207/10249013/10249834.pdf?arnumber=10249834

Reference22 articles.

1. Facial Emotion Recognition with Inter-Modality-Attention-Transformer-Based Self-Supervised Learning

2. Emotion Classification Using Convolutional Neural Networks;septian;In Proceedings of the National Seminar on Electrical Engineering at UIN Sunan Gunung Djati Bandung,2020

3. Identity-aware convolutional neural networks for facial expression recognition

4. Incremental boosting convolutional neural network for facial action unit recognition;han;Advances in neural information processing systems,2016

5. Fall Detection Based on RetinaNet and MobileNet Convolutional Neural Networks

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