The VHS project proposes a new approach to the historical study of the circulation of scientific knowledge based on new methods of illustration analysis. Thanks to the recent developments in AI, and Computer Vision, the aim is to design a new analysis tool based on the study of the evolution and transformation of images in illustrated scientific corpora from the Middle Ages and the modern period.

To this end, we will develop unsupervised or weakly supervised learning methods that will allow us to carry out large-scale automatic searches adapted to these corpora, based on the detection of iconographic similarities (between images, in order to identify the copying and borrowing processes, in particular) and textual similarities (between images and captions or associated texts, in order to identify, e.g., different images describing similar textual content). These methods will provide historians with new associations of illustrations and possible relationships (inter-iconic and/or inter-textual), the analysis of which will allow to conduct new works and initiate new dynamics of study on the role of image in construction and diffusion of scientific knowledge processes.

The project brings together three recognized partners (the Digital Humanities team of the Institut des Sciences du Calcul et des Données at Sorbonne University; the Monde Byzantin team from the Orient & Méditerranée laboratory (UMR 8167); the Imagine team from the Gaspard Monge Computer Science Laboratory at École des Ponts ParisTech (ENPC)) which brings together specialists in History of Science, scientific illustration, Computer Vision and Deep Learning.

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