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Springstein, Matthias; Schneider, Stefanie ORCID: 0000-0003-4915-6949; Rahnama, Javad; Hüllermeier, Eyke ORCID: 0000-0002-9944-4108; Kohle, Hubertus ORCID: 0000-0003-3162-1304; Ewerth, Ralph ORCID: 0000-0003-0918-6297 (October 2021): iART: A Search Engine for Art-Historical Images to Support Research in the Humanities. 29th ACM International Conference on Multimedia, October 20 - 24, 2021, Virtual.
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In this paper, we introduce iART: an open Web platform for art-historical research that facilitates the process of comparative vision. The system integrates various machine learning techniques for keyword- and content-based image retrieval as well as category formation via clustering. An intuitive GUI supports users to define queries and explore results. By using a state-of-the-art cross-modal deep learning approach, it is possible to search for concepts that were not previously detected by trained classification models. Art-historical objects from large, openly licensed collections such as Amsterdam Rijksmuseum and Wikidata are made available to users.