Over the last 10 years, the field of computer vision, which seeks to gain a high-level understanding of images using computational techniques, has seen rapid innovation. For example, computer vision models are able to locate and identify people, animals and thousands of objects on images with high levels of accuracy.

This technological innovation promises the same innovation for images that the combination of Optical Character Recognition/NLP (Natural language processing) techniques caused for texts. They open up a part of the digital archive for large-scale analysis, which, until now, has been left uncovered: the millions of images in digitized books, newspapers, periodicals, and historical documents.

This workshop will:

• Provide an introduction to deep learning based computer vision methods for humanities research.
• Give an overview of the steps involved in training a deep learning model.
• Discuss some of the specific considerations around using deep learning/computer vision for humanities research.
• Help you decide whether deep learning might be a useful tool for you.

Intended Audience

Researchers, curators and librarians interested in using computer vision with digitised visual materials.

Suggested Pre-requisites

You are welcome to join without the below experience:

Basic familiarity with Python or another programming language will be helpful, but in no way essential.

Basic familiarity with using Jupyter Notebooks i.e. knowing how to run the code included in a Jupyter notebook. Reading through this lesson from Programming Historian 'Introduction to Jupyter Notebooks' would be enough prior to the session.

Technical Requirements

Participants will need a laptop or personal computer with internet access and a modern browser (Firefox or Chrome preferred). It might be possible to follow materials with a tablet but we won’t be able to troubleshoot issues with this kind of setup.

Registering Your Interest

There are a limited number of places available for this course. Your application will be treated as an expression of interest and you are not guaranteed a place at the workshop.

As part of the application process, you will be asked to provide a brief explanation of how attending this workshop will benefit your research. You may find it useful to write this piece before attempting to register for the event.

After the application deadline has passed, submissions will be considered, and successful applicants will be offered a place by 30 March.

This process will help to ensure that each of the N8 universities are represented at, and benefit from the course.

This event is only open to those working or studying at one of the N8 Research Partnership universities. Please use your academic (.ac.uk) e-mail address to register for this event.