Multi-modal multi-view emotion detection using non-negative matrix factorisation

dc.contributor.author	GROZAVU, Nistor
dc.contributor.author	KHALAFAOUI, Yasser
dc.contributor.author	ROGOVSCHI, Nicoleta
dc.date.accessioned	2022-12-29T11:53:22Z
dc.date.available	2022-12-29T11:53:22Z
dc.date.issued	2022
dc.identifier.citation	GROZAVU, Nistor, KHALAFAOUI, Yasser, ROGOVSCHI, Nicoleta. Multi-modal multi-view emotion detection using non-negative matrix factorisation. In: Electronics, Communications and Computing (IC ECCO-2022): 12th intern. conf., 20-21 Oct. 2022, Chişinău, Republica Moldova: conf. proc., Chişinău, 2022, pp. 21.	en_US
dc.identifier.uri	http://repository.utm.md/handle/5014/21892
dc.description	Only Abstract
dc.description.abstract	Through this work we explore the unsupervised topological learning of multimodal data presenting a complex structure allowing to learn their representations. We are particularly interested in heterogeneous data whose representation may have been informed in different ways: expert representation which may be complex.	en_US
dc.language.iso	en	en_US
dc.publisher	Technical University of Moldova	en_US
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 United States	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.subject	multimodal data	en_US
dc.subject	unsupervised topological learning	en_US
dc.title	Multi-modal multi-view emotion detection using non-negative matrix factorisation	en_US
dc.type	Article	en_US