Working with Digital Data

in Religious Studies

11. Advanced Processing & AI: Process Images and Recognize Text

Summer Semester 2024
Prof. Dr. Nathan Gibson

Outline

  1. Review: Big Data & Machine Learning

  2. In-depth: Large Language Models

    –Break–

  3. Image processing principles
  4. Image processing examples

Next week in-person (for those who can)

My office (IG 6.552)

Project & Presentation

Sign up in OLAT

5 minutes:

  1. What is the format and source of your data? (Include critical reflection.)
  2. How did you edit, process, filter, or add to it? Why? (Show how you have used at least one of the approaches we discussed in class.)
  3. What is the most interesting question you might answer with your dataset?
  4. What is the most valuable thing you learned in the process?

A few slides or screen-sharing is allowed, but make sure you can keep it to 5 minutes!

Term Papers (Hausarbeit)

Please set up a meeting with me if you haven’t already.

  • Mondays 15:00-16:00 (in person, IG 6.552) sign-up
  • Fridays 12:00-13:00 (via Zoom) sign-up

Review: Principles of AI/Machine Learning: Big Data

Big Data: Data that defies “traditional methods” of processing or analysis because of its large scale.

Review: Principles of AI/Machine Learning: Machine Learning

Machine Learning: A process of using data to train software to recognize or predict patterns in new data

Machine Learning Process

Review: Principles of AI/Machine Learning: Machine Learning

Ground truth: Correctly labeled data used for training and testing

Neural networks use a process that turns nodes on or off based on many different inputs, and then goes back and refines the “weight” of these inputs.

Large language models predict the next word(s) after having been trained on a very large dataset.

In-depth: Large language models

Lee, Timothy B. “A Jargon-Free Explanation of How AI Large Language Models Work.” Ars Technica, July 31, 2023. https://arstechnica.com/science/2023/07/a-jargon-free-explanation-of-how-ai-large-language-models-work/.

Break

Image processing principles: Questions to ask

  • Purpose
  • Source
  • Access
  • Format
  • Manual or automatic processing

Image processing principles: Tasks

  • classification
  • object recognition
  • text recognition
  • color recognition
  • spatial dimensions

Image processing examples

https://recogito.pelagios.org/document/sapfxiswsuxh3b

Preview

Advanced Processing & AI: Generate and Transcribe Audio and Video