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Artificial intelligence for content and context metadata retrieval in photographs and image groups
Journal of Digital Media Management,
9
(4),
297-304
(2021)
Abstract
Cataloguing is a frequent bottleneck in the digitisation of analogue images as it is impossible to scale the necessary content-related knowledge. As this paper discusses, however, it is possible to use well-trained artificial intelligence to semi-automate metadata enhancement for photographic collections. The paper describes a study in which participants indexed historical collections of photographs. In a subsequent interdisciplinary project with contributions from cultural anthropologists, computer scientists, digital humanities researchers and art historians, these descriptions and indexes were then used to train machine-learning components. With this interdisciplinary approach, it is hoped that cataloguing practices can be enhanced, generating new insights into AI and semantic metadata.
Keywords: Machine learning; analogue and digital photography; cultural heritage; semantic metadata; cbir; iiif; curation
The full article is available to subscribers to the journal.
Author's Biography
Peter Fornaro is a member of the management team at the University of Basel’s Digital Humanities Lab. His research focuses on digital archiving, imaging, cultural heritage preservation and computational photography. In addition to research and lecturing, he provides consultancy to companies, archives and museums. Peter is also a member of the Swiss Commission for Cultural Heritage Preservation.
Vera Chiquet is a scientific assistant at the University of Basel’s Digital Humanities Lab and Data and Service Centre for the Humanities. She has taught and researched in Basel, Hamburg and Bologna. Her research focuses on mass media, photography and digitisation. She is President of the Friends of the Herzog Foundation, Laboratory of Photography.
