MULTIMODAL SYSTEM FOR FACIAL EMOTION RECOGNITION BASED ON DEEP LEARNING

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creativework.keywordsbody gesture recognition, deep learning neural network, facial emotion recognition, weather recognition
creativework.publisherUniversity of Chemical Technology and Metallurgyen
dc.contributor.authorAtanassov A.
dc.contributor.authorPilev D.
dc.contributor.authorTomova F.
dc.date.accessioned2024-07-10T14:27:06Z
dc.date.accessioned2024-07-10T14:51:33Z
dc.date.available2024-07-10T14:27:06Z
dc.date.available2024-07-10T14:51:33Z
dc.date.issued2024-01-01
dc.description.abstractEmotions are one of the main ways of communication between people and of expressing attitudes towards objects, products, services, etc. They are divided to verbal and non-verbal classes. Human speech and intonation belong to the first class, and to the second (non-verbal) facial and body emotions, known as body language. The subject of this report is the development of multimodal deep learning system intended to recognize facial and body emotions and their relationship with the scene (weather) in which they occur. It is based on three deep learning neural networks (DNN) each one for recognition of facial emotion, body emotion and weather. Combining their results, we improve significantly the final facial emotion recognition (FER) results.
dc.identifier.doi10.59957/jctm.v59.i3.2024.29
dc.identifier.issn1314-7978
dc.identifier.issn1314-7471
dc.identifier.scopusSCOPUS_ID:85193465707en
dc.identifier.urihttps://rlib.uctm.edu/handle/123456789/952
dc.language.isoen
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85193465707&origin=inward
dc.titleMULTIMODAL SYSTEM FOR FACIAL EMOTION RECOGNITION BASED ON DEEP LEARNING
dc.typeArticle
oaire.citation.issue3
oaire.citation.volume59
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