Proceeding of the Electrical Engineering Computer Science and Informatics
Vol 6: EECSI 2019

The Improved Artificial Neural Network Based on Cosine Similarity in Facial Emotion Recognition

Kirana, Kartika Candra (Universitas Negeri Malang)
Wibawanto, Slamet (Universitas Negeri Malang)
Hidayah, Nur (Universitas Negeri Malang)
Cahyono, Gigih Prasetyo (Software Engineering Visionet Data International)

Article Info

Publish Date
18 Sep 2019

Abstract

In this study, we present the improved artificial neural network based on cosine similarity in facial emotion recognition. We apply a shifting window that employs neural network for two concurrent processes consisting of face detection and emotional recognition. In order to prevent the slow and futile computations, non-face areas need to be filtered from neurons on each network layer, thus we propose the improved artificial neural network based on cosine similarity. Cosine similarity is employed to bypass the process of non-face areas in neural network. The accuracy of the proposed method reaches 0.84, while the accuracy of the original neural network method reaches 0.74. It can be concluded that our methods work accurately.proposed method is superior to the state-of-the-art algorithms.

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Journal Info
Proceeding of the Electrical Engineering Computer Science and Informatics
Website

Abbrev

EECSI

Publisher

IAES Indonesia Section and Partners

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Proceeding of the Electrical Engineering Computer Science and Informatics publishes papers of the "International Conference on Electrical Engineering Computer Science and Informatics (EECSI)" Series in high technical standard. The Proceeding is aimed to bring researchers, academicians, scientists, ...