Emotion Recognition using AutoEncoders and Convolutional Neural Networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F18%3A63520522" target="_blank" >RIV/70883521:28140/18:63520522 - isvavai.cz</a>

Result on the web

<a href="https://mendel-journal.org/index.php/mendel/article/view/31" target="_blank" >https://mendel-journal.org/index.php/mendel/article/view/31</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.13164/mendel.2018.1.113" target="_blank" >10.13164/mendel.2018.1.113</a>

Result language

angličtina

Original language name

Emotion Recognition using AutoEncoders and Convolutional Neural Networks

Original language description

Emotions demonstrate people&apos;s reactions to certain stimuli. Facial expression analysis is often used to identify the emotion expressed. Machine learning algorithms combined with artificial intelligence techniques have been developed in order to detect expressions found in multimedia elements, including videos and pictures. Advanced methods to achieve this include the usage of Deep Learning algorithms. The aim of this paper is to analyze the performance of a Convolutional Neural Network which uses AutoEncoder Units for emotion-recognition in human faces. The combination of two Deep Learning techniques boosts the performance of the classification system. 8000 facial expressions from the Radboud Faces Database were used during this research for both training and testing. The outcome showed that five of the eight analyzed emotions presented higher accuracy rates, higher than 90%.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Mendel

ISSN

1803-3814

e-ISSN

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Volume of the periodical

24

Issue of the periodical within the volume

1

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

8

Pages from-to

113-120

UT code for WoS article

—

EID of the result in the Scopus database

2-s2.0-85072024940