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Understanding Garda...
Understanding Gardar Sahlberg with neural nets : On algorithmic reuse of the Swedish SF archive
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- Eriksson, Maria, 1988- (författare)
- Umeå universitet,Humlab,Basel University, Department of Art, Media and Philosophy, Switzerland
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- Skotare, Tomas (författare)
- Umeå universitet,Humlab
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- Snickars, Pelle (författare)
- Lund University, Sweden
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(creator_code:org_t)
- Intellect Ltd. 2022
- 2022
- Engelska.
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Ingår i: Journal of Scandinavian Cinema. - : Intellect Ltd.. - 2042-7891 .- 2042-7905. ; 12:3, s. 225-247
- Relaterad länk:
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https://urn.kb.se/re...
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visa fler...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- HUMANIORA -- Konst -- Filmvetenskap (hsv//swe)
- HUMANITIES -- Arts -- Studies on Film (hsv//eng)
Nyckelord
- AI
- archival reuse
- computational film studies
- convolutional neural nets
- film archives
- Video Reuse Detector
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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