Synthetic images : data-based aesthetics

Detalhes bibliográficos
Autor(a) principal: Lee, Rosemary
Data de Publicação: 2023
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10437/14559
Resumo: This essay examines how data-based practices contribute to new perspectives on the empirical value of images. Recent methods employing machine learning enable visualisations to be produced based on the large-scale analysis of data but that are detached from direct sensorial observation, subverting the forms of visual objectivity traditionally associated with technical and scientific methods of image-making. This research aims to develop insights into the forms of visual knowledge that these methods may give rise to, as well as facilitating critical discourse on the grounding of visual practices in relation to technical and scientific methods.
id RCAP_07d7e444f1c38626d54e187fcda5f3f5
oai_identifier_str oai:recil.ensinolusofona.pt:10437/14559
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Synthetic images : data-based aestheticsAUDIOVISUALAPRENDIZAGEM COMPUTACIONALEPISTEMOLOGIAESTÉTICA DIGITALVISUALIZAÇÃO DE DADOSCOMPUTAÇÃO VISUALAUDIOVISUALMACHINE LEARNINGEPISTEMOLOGYDIGITAL AESTHETICSDATA VISUALIZATIONVISUAL COMPUTINGThis essay examines how data-based practices contribute to new perspectives on the empirical value of images. Recent methods employing machine learning enable visualisations to be produced based on the large-scale analysis of data but that are detached from direct sensorial observation, subverting the forms of visual objectivity traditionally associated with technical and scientific methods of image-making. This research aims to develop insights into the forms of visual knowledge that these methods may give rise to, as well as facilitating critical discourse on the grounding of visual practices in relation to technical and scientific methods.Universidade Lusófona2024-03-11T15:21:26Z2023-12-01T00:00:00Z2023-12info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10437/14559enghttps://doi.org/10.60543/liveinterfacesjournal.v1i1.9143Lee, Rosemaryinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-15T01:38:29Zoai:recil.ensinolusofona.pt:10437/14559Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T04:01:01.886906Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Synthetic images : data-based aesthetics
title Synthetic images : data-based aesthetics
spellingShingle Synthetic images : data-based aesthetics
Lee, Rosemary
AUDIOVISUAL
APRENDIZAGEM COMPUTACIONAL
EPISTEMOLOGIA
ESTÉTICA DIGITAL
VISUALIZAÇÃO DE DADOS
COMPUTAÇÃO VISUAL
AUDIOVISUAL
MACHINE LEARNING
EPISTEMOLOGY
DIGITAL AESTHETICS
DATA VISUALIZATION
VISUAL COMPUTING
title_short Synthetic images : data-based aesthetics
title_full Synthetic images : data-based aesthetics
title_fullStr Synthetic images : data-based aesthetics
title_full_unstemmed Synthetic images : data-based aesthetics
title_sort Synthetic images : data-based aesthetics
author Lee, Rosemary
author_facet Lee, Rosemary
author_role author
dc.contributor.author.fl_str_mv Lee, Rosemary
dc.subject.por.fl_str_mv AUDIOVISUAL
APRENDIZAGEM COMPUTACIONAL
EPISTEMOLOGIA
ESTÉTICA DIGITAL
VISUALIZAÇÃO DE DADOS
COMPUTAÇÃO VISUAL
AUDIOVISUAL
MACHINE LEARNING
EPISTEMOLOGY
DIGITAL AESTHETICS
DATA VISUALIZATION
VISUAL COMPUTING
topic AUDIOVISUAL
APRENDIZAGEM COMPUTACIONAL
EPISTEMOLOGIA
ESTÉTICA DIGITAL
VISUALIZAÇÃO DE DADOS
COMPUTAÇÃO VISUAL
AUDIOVISUAL
MACHINE LEARNING
EPISTEMOLOGY
DIGITAL AESTHETICS
DATA VISUALIZATION
VISUAL COMPUTING
description This essay examines how data-based practices contribute to new perspectives on the empirical value of images. Recent methods employing machine learning enable visualisations to be produced based on the large-scale analysis of data but that are detached from direct sensorial observation, subverting the forms of visual objectivity traditionally associated with technical and scientific methods of image-making. This research aims to develop insights into the forms of visual knowledge that these methods may give rise to, as well as facilitating critical discourse on the grounding of visual practices in relation to technical and scientific methods.
publishDate 2023
dc.date.none.fl_str_mv 2023-12-01T00:00:00Z
2023-12
2024-03-11T15:21:26Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10437/14559
url http://hdl.handle.net/10437/14559
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://doi.org/10.60543/liveinterfacesjournal.v1i1.9143
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Universidade Lusófona
publisher.none.fl_str_mv Universidade Lusófona
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
_version_ 1799138184819376128

Registros relacionados