BYU

Abstract by Jesse Williams

Personal Infomation


Presenter's Name

Jesse Williams

Co-Presenters

Jesse Williams
Daniel Segrera

Degree Level

Undergraduate

Co-Authors

Joshua Hunt
Daniel Segrera

Abstract Infomation


Department

Computer Science

Faculty Advisor

Mark Clement

Title

Handwriting Recognition

Abstract

Handwriting recognition was once a very human task—computers have never been very good at complex pattern recognition in the way that humans are. However, in recent decades, advances in machine learning have facilitated the automation of handwriting recognition. Our research has been focused on reading historical documents, including US censuses. These documents present many unique challenges. For example, tabular data like census records are easier to read when segmented into table cells, which opens up possibilities for research about table segmentation. After cells are segmented, the handwriting in them must be read. Using transfer learning we hope to be able to apply the generalized deep learning model we create to various unrelated writing applications. The results of such research can be seen in apps like VetFinder.