DominikBoenisch/Training-the-Archive
Research project combining artificial intelligence and museum collection data through machine learning and object recognition.
This project helps art historians and curators discover hidden connections within large museum collections. It takes digital images of artworks and curatorial input on relationships between pieces, then outputs visual clusters and networks of similar or related artworks. Curators, art researchers, and collection managers can use this to explore collections in new ways.
No commits in the last 6 months.
Use this if you are a curator or art researcher looking to uncover non-obvious patterns, associations, or stylistic links across a vast digital art archive.
Not ideal if you need a simple search tool for known artworks or if your collection consists primarily of text-based documents rather than visual art.
Stars
26
Forks
1
Language
Jupyter Notebook
License
GPL-3.0
Category
Last pushed
Oct 04, 2021
Commits (30d)
0
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