Visual emotion sensing using convolutional neural network

• Autorzy: Ayadi, Souha , Lachiri, Zied

Warianty tytułu

PL

Wizualne wykrywanie emocji za pomocą splotowej sieci neuronowej

• Języki publikacji: EN

Abstrakty

EN

The objective of this article is to present a CNN architecture relevant to the Interactive Emotional Dyadic Motion Capture (IEMOCAP). Since the database showed some issues during the training phase, we are using frames as inputs instead of video recorder to minimize the error and increase the accuracy. We apply the methodology of transfer learning by adjust the number of layers and the weight of the database. The results of the female and male genders are 91% and 89% respectively.

PL

Celem tego artykułu jest przedstawienie architektury CNN odpowiedniej do interaktywnego emocjonalnego przechwytywania ruchu (IEMOCAP). Ponieważ baza danych wykazała pewne problemy w fazie uczenia, używamy klatek jako danych wejściowych zamiast rejestratora wideo, aby zminimalizować błąd i zwiększyć dokładność. Stosujemy metodologię transferu uczenia się dostosowując liczbę warstw i wagę bazy danych. Wyniki dla płci żeńskiej i męskiej wynoszą odpowiednio 91% i 89%.

Słowa kluczowe

PL

wizualne rozpoznawanie emocji; CNN

EN

visual emotion recognition; CNN

• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2022
• Tom: R. 98, nr 3
• Strony: 89--92
• Opis fizyczny: Bibliogr. 17 poz., il., rys., tab.

Twórcy

autor

Ayadi, Souha

• Signal Image and Information Technology(SITI) Laboratory, Department of Electrical Engineering, National Engineering School of Tunis, Campus Universitaire Farhat Hached el Manar BP 37, Le Belvedere 1002 TUNIS,

autor

Lachiri, Zied

• Signal Image and Information Technology(SITI) Laboratory, Department of Electrical Engineering, National Engineering School of Tunis, Campus Universitaire Farhat Hached el Manar BP 37, Le Belvedere 1002 TUNIS,

Bibliografia

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• [14] Yanting Pei, Yaping Huang, Qi Zou, Xingyuan Zhang, and Song Wang. Effects of image degradation and degradation removal to cnn-based image classification.IEEE transactions on pattern analysis and machine intelligence, 2019.
• [15] M Shamim Hossain and Ghulam Muhammad. Emotion recognition using deep learning approach from audio–visual emotional big data. Information Fusion, 49:69–78, 2019.
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Identyfikatory

DOI

10.15199/48.2022.03.20