DHNord2020 - Call for papers

DHNord2020: The Measurement of Images: Computational Approaches in the History and Theory of the Arts

The DHNord colloquium brings together the digital humanities community every year at the Maison Européenne des Sciences de l'Homme et de la Société in Lille. The theme chosen for 2020 considers computational approaches to images in the history and theory of the arts. This conference will bring together for the first time in France the leading specialists in artificial intelligence applied to the arts. The history of arts and culture, as well as aesthetics, have greatly benefited in recent years from the results of heritage digitization campaigns. Since 2013, digital art history has experienced unprecedented growth, particularly in the Anglo-Saxon spheres and in Europe (Joyeux-Prunel, Drucker 2013, Zorich 2012). While the analysis of texts has long been favored by the digital humanities, it is now becoming possible to carry out computational analyses on the very matter of images, or even on 3D objects, which constitutes a major turning point. This colloquium will explore how computational methods are renewing traditional questions of art history, aesthetics and visual culture (creative process, style, form, attribution, iconology, circulation of works, etc.) and raising new research questions for our disciplines (visual arts, architecture, theatre, cinema, photography, etc.) at a time when new tools are becoming available to researchers.

Papers may address the following topics: uses of artificial intelligence (especially deep learning and machine learning) applied to image corpora, data construction, and processing issues, epistemological questions related to the selection of training corpora and the use of tools, historical evolution of the field, renewal of research questions, availability of corpora, reproducibility of research and sharing of models. The invitation to foreign speakers and the need to exchange our work in an international context implies that the language used for oral communications will be English. Proposals can be sent in both French and English.

Submissions may include:

20-minute presentations, which will then be organized in thematic sessions. (abstract: 500 words, excluding references)

Posters / demos. (abstract: 750 words, excluding references)

Please submit your proposal at: https://dhnord2020.sciencesconf.org/

A collective book resulting from the conference will be published by the Presses Universitaires du Septentrion and will be available in Open Access. We encourage authors to publish the datasets and the computer code jointly. In order to facilitate a quick edition and to favor exchanges during the conference, the final texts, in French or in English, will be due by 01/10/2020.

The current health situation will probably lead us to adapt the traditional face-to-face format of the conference.

Calendar:

05/06/2020: abstract deadline

20/06/2020: notification of acceptances

01/10/2020: paper submission deadline

Chairs: Clarisse Bardiot and Emmanuel Château-Dutier

Scientific Committee:

Elise Baillieul (ULille)

Clarisse Bardiot (UPHF, MESHS)

Emmanuel Château-Dutier (Université de Montréal, CRIHN)

Antoine Courtin (INHA)

Océane Delleaux (ULille)

Béatrice Joyeux-Prunel (University of Geneva)

Nicolas Hervé (INA)

Kristin Tanton (Université de Montréal, CRIHN)

Nicolas Thély (University of Rennes, MSHB)

Indicative bibliography

Arnold, Taylor, and Lauren Tilton. n.d. “Distant Viewing: Analyzing Large Visual Corpora.” Digital Scholarship in the Humanities. Accessed May 10, 2020. https://doi.org/10.1093/digitalsh/fqz013.

Drucker, Johanna. 2013. “Is There a ‘Digital’ Art History?” Visual Resources 29 (1–2, Digital Art History): 5–13. https://doi.org/10.1080/01973762.2013.761106.

Ellis, Margaret Holben, and C. Richard Johnson Jr. 2019. “Computational Connoisseurship: Enhanced Examination Using Automated Image Analysis.” Visual Resources 35 (1–2, Digital Art History): 125–40. https://doi.org/10.1080/01973762.2019.1556886.

Impett, Leonardo, and Franco Moretti. 2017. Totentanz. Operationalizing Aby Warburg’s ‘Pathosformeln.’ Literary Lab Pamphlet 16. https://litlab.stanford.edu/LiteraryLabPamphlet16.pdf.

Joyeux-Prunel, Béatrice. 2010. L’art et la mesure : histoire de l’art et méthodes quantitatives. Actes de la recherche à l’Ens 5. Paris: Éditions Rue d’Ulm ; Presses de l’École normale supérieure.

Klinke, Harald and Liska Surkemper, eds. 2016. Visualising big image data. International Journal of Digital Art History.

Manovich, Lev. 2012. “How to Compare One Million Images?” In Understanding Digital Humanities, edited by David M. Berry, 249–78. London: Palgrave Macmillan UK. https://doi.org/10.1057/9780230371934_14.

Rodríguez-Ortega, Nuria. 2020.  “Image processing and computer vision in the field of digital art history.” In The Routledge Companion to Digital Humanities and Art History. Brown, Kathryn, ed. Routledge Art History and Visual Studies Companions. New York: Routledge.

Seguin, Benoit. 2018. “The Replica Project: Building a Visual Search Engine for Art Historians.” XRDS 24 (3): 24–29. https://doi.org/10.1145/3186653.

Shen, Xi, Alexei A. Efros, and Mathieu Aubry. 2019. “Discovering Visual Patterns in Art Collections with Spatially-Consistent Feature Learning.” ArXiv:1903.02678 [Cs], March. http://arxiv.org/abs/1903.02678.

Vane, Olivia. 2019. “Timeline Design For Visualising Cultural Heritage Data.” PhD Thesis, Innovation Design Engineering, Londres: Royal College of Art. http://oliviavane.co.uk/research/about.html.

Wevers, Melvin, and Thomas Smits. n.d. “The Visual Digital Turn: Using Neural Networks to Study Historical Images.” Digital Scholarship in the Humanities. Accessed February 3, 2019. https://doi.org/10.1093/llc/fqy085.