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dc.contributor.authorMagdin, Martin
dc.contributor.authorPrikler, F
dc.date2019-03
dc.date.accessioned2022-02-14T10:32:31Z
dc.date.available2022-02-14T10:32:31Z
dc.identifier.issn1989-1660
dc.identifier.urihttps://reunir.unir.net/handle/123456789/12437
dc.description.abstractAt the present time, various freely available or commercial solutions are used to classify the subject's emotional state. Classification of the emotional state helps us to understand how the subject feels and what he is experiencing in a particular situation. Classification of the emotional state can thus be used in various areas of our life from neuromarketing, through the automotive industry (determining how emotions affect driving), to implementing such a system into the learning process. The learning process, which is the (mutual) interaction between the teacher and the learner, is an interesting area in which individual emotional states can be explored. In this pedagogical-psychological area several research studies were realized. These studies in some cases demonstrated the important impact of the emotional state on the results of the students. However, for comparison and unambiguous classification of the emotional state most of these studies used the instructed (even constructed) stereotypical facial expressions of the most well-known test databases (Jaffe is a typical example). Such facial expressions are highly standardized, and the software can recognize them with a fairly big percentage, but this does not necessarily point to the actual success rate of the subject's emotional classification in such a test because the similarity to real emotional expression remains unknown. Therefore, we examined facial expressions in real situations. We have subsequently compared these examined facial expressions with the instructed expressions of the same emotions (the Jaffe database). The overall average classification score in real facial expressions was 94.58%.es_ES
dc.language.isoenges_ES
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)es_ES
dc.relation.ispartofseries;vol. 5, nº 4
dc.relation.urihttps://www.ijimai.org/journal/bibcite/reference/2662es_ES
dc.rightsopenAccesses_ES
dc.subjectface detectiones_ES
dc.subjectfacial expressiones_ES
dc.subjectemotiones_ES
dc.subjectinstructed stimulies_ES
dc.subjectreal-life stimulies_ES
dc.subjectIJIMAIes_ES
dc.titleAre Instructed Emotional States Suitable for Classification? Demonstration of How They Can Significantly Influence the Classification Result in An Automated Recognition Systemes_ES
dc.typearticlees_ES
reunir.tag~IJIMAIes_ES
dc.identifier.doihttp://doi.org/10.9781/ijimai.2018.03.002


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