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 SM ISO690:2012ALBU, Veaceslav. Measuring human emotions with modular neural networks. In: International Multi-Conference on Complexity, Informatics and Cybernetics: IMCIC, 8-11 martie 2016, Orlando. Florida, U.S.A.: International Institute of Informatics and Systemics, IIIS, 2016, Ediția 7, Vol.1, pp. 26-27. ISBN 978-194176334-6. |
| EXPORT metadate: Google Scholar Crossref CERIF DataCite Dublin Core |
| International Multi-Conference on Complexity, Informatics and Cybernetics Ediția 7, Vol.1, 2016 |
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Conferința "7th International Multi-Conference on Complexity, Informatics and Cybernetics and 7th International Conference on Society and Information Technologies" Orlando, Statele Unite ale Americii, 8-11 martie 2016 | ||||||
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| Pag. 26-27 | ||||||
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In this paper, we propose a hybrid architecture for detection of human emotions. The architecture represents an effective tool for real-time processing of customer's behaviour for distributed on-land systems, such as kiosks and ATMs. The proposed approach combines most recent biometric techniques with the NN approach for real-time emotion and behavioural analysis. The architecture of the system represents the combination of radial basis function neural networks with selforganised maps (RBF-SOM). |
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| Cuvinte-cheie computer vision, Emotion classification, Neural networks, RBFNN |
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Dublin Core Export
<?xml version='1.0' encoding='utf-8'?> <oai_dc:dc xmlns:dc='http://purl.org/dc/elements/1.1/' xmlns:oai_dc='http://www.openarchives.org/OAI/2.0/oai_dc/' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xsi:schemaLocation='http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd'> <dc:creator>Albu, V.A.</dc:creator> <dc:date>2016</dc:date> <dc:description xml:lang='en'><p>In this paper, we propose a hybrid architecture for detection of human emotions. The architecture represents an effective tool for real-time processing of customer's behaviour for distributed on-land systems, such as kiosks and ATMs. The proposed approach combines most recent biometric techniques with the NN approach for real-time emotion and behavioural analysis. The architecture of the system represents the combination of radial basis function neural networks with selforganised maps (RBF-SOM).</p></dc:description> <dc:source>International Multi-Conference on Complexity, Informatics and Cybernetics (Ediția 7, Vol.1) 26-27</dc:source> <dc:subject>computer vision</dc:subject> <dc:subject>Emotion classification</dc:subject> <dc:subject>Neural networks</dc:subject> <dc:subject>RBFNN</dc:subject> <dc:title>Measuring human emotions with modular neural networks</dc:title> <dc:type>info:eu-repo/semantics/article</dc:type> </oai_dc:dc>
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