  Nowadays, one of the critical challenges in forensics is analyzing the
enormous amounts of unstructured digital evidence, such as images. Often,
unstructured digital evidence contains precious information for forensic
investigations. Therefore, a retrieval system that can effectively identify
forensically relevant images is paramount. In this work, we explored the
effectiveness of interactive learning in improving image retrieval performance
in the forensic domain by proposing Excalibur - a zero-shot cross-modal image
retrieval system extended with interactive learning. Excalibur was evaluated
using both simulations and a user study. The simulations reveal that
interactive learning is highly effective in improving retrieval performance in
the forensic domain. Furthermore, user study participants could effectively
leverage the power of interactive learning. Finally, they considered Excalibur
effective and straightforward to use and expressed interest in using it in
their daily practice.

Information Retrieval;Human-Computer Interaction