Hybrid image retrieval in digital libraries: A large scale multicollection experimentation of deep learning techniques

Abstract

While digital heritage libraries historically took advantage of OCR to index their printed collections, the access to iconographic resources has not progressed in the same way, and the latter remain in the shadows. Today, it would be possible to make better use of these resources, especially by leveraging the illustrations recognized thanks to the OCR produced during the last two decades. This work presents an ETL (extract-transform-load) approach to this need, that aims to: Identify iconography wherever it may be found; Enrich the illustrations metadata with deep learning approaches; Load it all into a web app for hybrid image retrieval.