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Authentication of Art: assessing the performance of a machine learning based authentication method

dc.contributor.authorChen, Ailin
dc.contributor.authorJesus, Rui
dc.contributor.authorVilarigues, Márcia
dc.date.accessioned2020-11-24T10:26:49Z
dc.date.available2020-11-24T10:26:49Z
dc.date.issued2020-07-28
dc.description.abstractThis paper compares the test results generated by applying the method for the authentication of paintings by Portuguese artist Amadeo de Souza Car-doso in the interest of exploring the generalisation properties of the algorithm on other artists or genres. This sets the base for the method to be improved and de-veloped accordingly in future applications for a broader audience in a wider set-ting. The obtained results show that the classifier obtained from the algorithm using paintings appears not to be directly applicable to drawings of the same art-ist. When the classifier is retrained for a different genre like Chinese paintings or artists like van Gogh, the algorithm appears to perform as well as the classifier on Amadeo paintings, i.e. the algorithm is sufficient for the classification of a specific type of artist or genre.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationCHEN, Ailin; JESUS, Rui; VILARIGUES, Márcia – Authentication of Art: assessing the performance of a machine learning based authentication method. In ArtsIT 2019, DLI 2019: Interactivity, Game Creation, Design, Learning, and Innovation (Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 328)). Aalborg, Denmark: Springer, 2019. ISBN 978-3-030-53294-9. Vol. 328, pp. 328-342pt_PT
dc.identifier.doi10.1007/978-3-030-53294-9_22pt_PT
dc.identifier.isbn978-3-030-53294-9
dc.identifier.isbn978-3-030-53293-2
dc.identifier.urihttp://hdl.handle.net/10400.21/12394
dc.language.isoengpt_PT
dc.publisherSpringerpt_PT
dc.relationUID/CEC/04516/2019 - FCT/MEC NOVA LINCS PEstpt_PT
dc.relationPD/BD/135223/2017 - FCTpt_PT
dc.subjectAuthenticationpt_PT
dc.subjectPaintingspt_PT
dc.subjectDrawingspt_PT
dc.subjectMachine learningpt_PT
dc.subjectArtpt_PT
dc.titleAuthentication of Art: assessing the performance of a machine learning based authentication methodpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceNovember 6-8, 2019 - Aalborg, Denmarkpt_PT
oaire.citation.endPage342pt_PT
oaire.citation.startPage328pt_PT
oaire.citation.titleArtsIT 2019, DLI 2019: Interactivity, Game Creation, Design, Learning, and Innovationpt_PT
oaire.citation.volume328pt_PT
person.familyNameJesus
person.givenNameRui
person.identifier2682439
person.identifier.ciencia-id041D-93A6-7412
person.identifier.orcid0000-0003-1869-6491
person.identifier.scopus-author-id23012170100
rcaap.rightsclosedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationcfde72fc-2907-42d5-9b1e-93ddde41c3bd
relation.isAuthorOfPublication.latestForDiscoverycfde72fc-2907-42d5-9b1e-93ddde41c3bd

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