Computer vision for history: keyword detection in century old handwritten documents

Term: 
2022-2023 Spring
Faculty Department of Project Supervisor: 
Faculty of Engineering and Natural Sciences
Number of Students: 
4

Imagine being able to scan in minutes an archive of tens of thousands of documents for a given keyword! This would be invaluable for archivists and historians.
This project is about creating a computer vision program that will admit as input the digital image of a handwritten word, then scan a large database containing scanned images of handwritten documents, and return the documents containing that word as well as the word's location.
This is a textbook object detection challenge. You are expected to use modern deep learning techniques.
This project is most suitable for individuals with a keen interest in history and culture.
Students that have completed the EE417 (computer vision) course will be prioritized.

Financial support will be provided.
 
 

Related Areas of Project: 
Computer Science and Engineering
Electronics Engineering