This tutorial explores where and how to find, create, and collect images of textual material, a crucial initial step in any process using Automatic Text Recognition (ATR).
This talk gives an overview over developments in digital cultural heritage in recent decades and explores challenges, and opportunities, in the field. It addresses the importance of open, fair and democratic sharing of cultural data, challenges with sustainability of digital projects and how gaming can be a tool for public engagement.
This presentation outlines the aim and scope of the Historical Farm and People Registry project, explains the development process and problems encountered on the way, and demonstrates a use case for the ‘final’ product.
This lesson demonstrates how to build a basic interactive web application using Shiny, a library (a set of additional functions) for the programming language R. In the lesson, you will design and implement a simple application, consisting of a slider which allows a user to select a date range, which will then trigger some code in R, and display a set of corresponding points on an interactive map.
Kick off your journey into Automatic Text Recognition (ATR) with our introductory tutorial video. This is the first video of a tutorial series dedicated to extracting full text from scanned images.
This tutorial provides a comprehensive guide on using chroma keying, or green screen effects, with the PowerDirector video editing app, showing users how to set up the app, import footage, apply the chroma key effect, and export the final video.
This lesson from Programming Historian introduces basic use of Map Warper for historical maps. It guides you from upload to export, demonstrating methods for georeferencing and producing visualizations.
In this video, presented as part of the Friday Frontiers series, Bernard Pochet traces the evolution of Open Science at the University of Liège in the early 2000s, focusing on Open Access and the implementation of a Diamond Open Access journal publishing platform (PoPuPS) and an institutional repository (ORBi).
In this lesson, you will learn how to apply a Generative Pre-trained Transformer language model to a large-scale corpus so that you can locate broad themes and trends within written text.
This resource from the CLS INFRA project offers an introduction to several research areas and issues that are prominent withinComputational Literary Studies (CLS), including authorship attribution, literary history, literary genre, gender in literature, and canonicity/prestige, as well as to several key methodological concerns that are of importance when performing research in CLS.