Jan 17, 2018 5:30:00 PM
End: Jan 17, 2018 6:30:00 PM
The combination of qualitative and quantitative approaches (so-called “close reading” and “distant reading”) is seen by many as the way to proceed in Digital Humanities (cf. DH Manifesto 2.0). The ambition to reach across the science/humanities divide is echoed in industry, with the emphasis on “thick data” (Wang 2013) to complement “big data”, and in the Data Science community, with an increasing emphasis on human-centred Data Science, focussed on interpretability of machine learning models and a more active role of human input in algorithms (Chen et al. 2016).
Computer vision as critical practice: how digital humanities can teach computers to say what they see
Jan 31, 2018 5:30:00 PM
End: Jan 31, 2018 6:30:00 PM
Computer vision has made fundamental advances in recent years, but has only just begun to be adopted by digital humanists. This paper will outline some of its humanities applications, including how computational analysis relates to established descriptive practices. Examples will include popular print, early photography and scientific illustration within fields such as book history, conservation research and visual studies.