| Articolul precedent |
| Articolul urmator |
 |
 226 0 |
 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 |
||||||
|
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 | ||||||
|
||||||
| Pag. 26-27 | ||||||
|
||||||
 Descarcă PDF |
||||||
| Rezumat | ||||||
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). |
||||||
| Cuvinte-cheie computer vision, Emotion classification, Neural networks, RBFNN |
||||||
|
DataCite XML Export
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns='http://datacite.org/schema/kernel-3' xsi:schemaLocation='http://datacite.org/schema/kernel-3 http://schema.datacite.org/meta/kernel-3/metadata.xsd'> <creators> <creator> <creatorName>Albu, V.A.</creatorName> <affiliation>Institutul de Matematică şi Informatică al AŞM, Moldova, Republica</affiliation> </creator> </creators> <titles> <title xml:lang='en'>Measuring human emotions with modular neural networks</title> </titles> <publisher>Instrumentul Bibliometric National</publisher> <publicationYear>2016</publicationYear> <relatedIdentifier relatedIdentifierType='ISBN' relationType='IsPartOf'>978-194176334-6</relatedIdentifier> <subjects> <subject>computer vision</subject> <subject>Emotion classification</subject> <subject>Neural networks</subject> <subject>RBFNN</subject> </subjects> <dates> <date dateType='Issued'>2016</date> </dates> <resourceType resourceTypeGeneral='Text'>Conference Paper</resourceType> <descriptions> <description xml:lang='en' descriptionType='Abstract'><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></description> </descriptions> <formats> <format>application/pdf</format> </formats> </resource>
|
|
|
