Visual Navigation of Digitised Manuscripts
Exploring large collections of digitised manuscripts can be challenging for scholars, hindering their progress in answering research questions. In this research direction, we develop machine learning approaches to enable the visual navigation of digitised manuscripts and the automatic retrieval of relevant samples. This research includes topics such as visual-pattern detection, image clustering, and vision-language learning. By employing these advanced techniques, scholars can more effectively navigate and analyse vast digital archives, facilitating a deeper understanding and more efficient examination of historical texts.