iART: A Search Engine for Art-Historical Images to Support Research in the Humanities

Springstein, Matthias; Schneider, Stefanie ; Rahnama, Javad; Hüllermeier, Eyke ; Kohle, Hubertus und Ewerth, Ralph (Oktober 2021): iART: A Search Engine for Art-Historical Images to Support Research in the Humanities. 29th ACM International Conference on Multimedia, Virtual, October 20 - 24, 2021. In: Proceedings of the 29th ACM International Conference on Multimedia, S. 2801-2803

Abstract

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.

• Dokumententyp: Konferenzbeitrag (Paper)
• Publikationsform: Publisher's Version
• Fakultät: Mathematik, Informatik und Statistik > Informatik > Künstliche Intelligenz und Maschinelles Lernen
• Themengebiete: 000 Informatik, Informationswissenschaft, allgemeine Werke > 000 Informatik, Wissen, Systeme
• Sprache: Englisch