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Understanding Gardar Sahlberg with neural nets: On algorithmic reuse of the Swedish SF archive
Umeå universitet, Humanistiska fakulteten, Humlab. Basel University, Department of Art, Media and Philosophy, Switzerland.
Umeå universitet, Humanistiska fakulteten, Humlab.ORCID-id: 0000-0001-8445-0559
Lund University, Sweden.
2022 (Engelska)Ingår i: Journal of Scandinavian Cinema, ISSN 2042-7891, E-ISSN 2042-7905, Vol. 12, nr 3, s. 225-247Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

In this article, we re-trace the history of the Swedish SF archive and reflect on how this collection of historic newsreels has been reappropriated and remixed through-out more recent media history. In particular, we focus on the work of director and film historian Gardar Sahlberg, who made extensive use of the SF archive, first in a series of documentary films, then in a number of historical TV programmes. We are interested in how historic film footage travels and circulates through time, but foremost we explore how algorithms can help identify instances of audio-visual reuse in large datasets. Hence the article discusses algorithmic ways of examining archival film reuse, introducing a method for mapping video reuse with the help of artificial intelligence or more precisely machine learning that uses so-called convo-lutional neural nets. The article presents the Video Reuse Detector (VRD), a tool that uses machine learning to identify visual similarities within a given audiovisual database such as the SF archive.

Ort, förlag, år, upplaga, sidor
Intellect Ltd., 2022. Vol. 12, nr 3, s. 225-247
Nyckelord [en]
AI, archival reuse, computational film studies, convolutional neural nets, film archives, Video Reuse Detector
Nationell ämneskategori
Filmvetenskap
Identifikatorer
URN: urn:nbn:se:umu:diva-208064DOI: 10.1386/JSCA_00075_1ISI: 001023046000002Scopus ID: 2-s2.0-85153482909OAI: oai:DiVA.org:umu-208064DiVA, id: diva2:1760137
Tillgänglig från: 2023-05-29 Skapad: 2023-05-29 Senast uppdaterad: 2023-09-05Bibliografiskt granskad

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Eriksson, MariaSkotare, Tomas

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