JSTOR

Archives; Access and Artificial Intelligence, Working with Born-Digital and Digitized Archival Collections

Year

2022

Publisher

transcript Verlag

Language

English

Pages

33

Link

Last Update

04-Sep-2024

Keywords

Communication Studies

Description

Computer vision and computational art history are naturally synergistic fields. With the internet’s growing presence in modern life, art museums and cultural heritage institutions are digitizing their collections to connect to a wider and more inclusive audience through their websites and social media platforms and thus are releasing terabytes of high-quality, annotated digital images online. Meanwhile, state-of-the-art deep neural networks have achieved near human-level performance in the identification of the subject matter and formal qualities of digitized images, a performance predicated on the availability of large and fully labeled training datasets such as those produced by museum and art library...

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