State of the Art? Projects in the Digital Humanities [CV for DH, by Sarah Lang & Suzana Sagadin]

Описание: This video is part of the self-learning class "Computer Vision for Digital Humanists". Learn computer vision and deep learning basics, how to create your own ground truth for supervised learning, how to interpret and evaluate results of computer vision algorithms, guidelines on how to best handle Humanities data within CV, image management with Tropy, pre-processing your data set in python, moving from a first hello world ‘mini model’ to real-life ML.

The foundational skills in Distant Viewing and computer vision are increasingly relevant in the Digital Humanities, yet educational resources are often aimed at those with a background in computer science and statistics. For example, machine learning and digital image processing are fundamental to the Computational Humanities, but many scholars in the Digital Humanities lack accessible training in these areas.

The goal of this project was to create a focused course enabling students to acquire essential skills in computer vision, specifically tailored for Digital Humanists. Upon completing this course, students will possess a foundational understanding of digital image representation, computer vision methodologies, and machine learning techniques, all contextualized within the Digital Humanities framework. The workshop as an in-person event was used to create the materials which were made into this video class for self-study.

This video is part of the project "Computer Vision for Digital Humanists" ( https://dha.acdh.oeaw.ac.at/en/comput... ) and licensed Creative Commons BY NC SA. This project (2023) is funded by CLARIAH-AT with the support of BMBWF. It was made possible by major contributions from the ERC DiDip project (From Digital to Distant Diplomatics https://didip.hypotheses.org/ ). The video was produced by Moving Stills ( https://www.moving-stills.com/ ).