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

In this paper, we introduce iART: an open Web platform for arthistorical 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. Arthistorical objects from large, openly licensed collections such as Amsterdam Rijksmuseum and Wikidata are made available to users.