Publication
Image Sentiment Analysis: Experimental Evaluation of Several Deep Learning Architectures
| dc.contributor.author | Gaspar, António | |
| dc.contributor.author | Alexandre, Luís | |
| dc.date.accessioned | 2020-01-09T11:52:17Z | |
| dc.date.available | 2020-01-09T11:52:17Z | |
| dc.date.issued | 2019-10 | |
| dc.description.abstract | Image sentiment analysis is an important topic nowadays. It is possible to use it to classify an image at sentiment level, as negative, neutral or positive. However, to classify an image at this level is a hard challenge because its semantic meaning can represent many scenarios. In this paper, we present an analysis of several image classification methods that we evaluate to improve the state of the art in a large tweet data set. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.6/8155 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.title | Image Sentiment Analysis: Experimental Evaluation of Several Deep Learning Architectures | pt_PT |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | 25th Portuguese Conference on Pattern Recognition (RECPAD 2019) | pt_PT |
| person.familyName | Alexandre | |
| person.givenName | Luís | |
| person.identifier.ciencia-id | 2014-0F06-A3E3 | |
| person.identifier.orcid | 0000-0002-5133-5025 | |
| person.identifier.rid | E-8770-2013 | |
| person.identifier.scopus-author-id | 8847713100 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |
| relation.isAuthorOfPublication | 131ec6eb-b61a-4f27-953f-12e948a43a96 | |
| relation.isAuthorOfPublication.latestForDiscovery | 131ec6eb-b61a-4f27-953f-12e948a43a96 |