CSCE Capstone
Student Site for Individual and Collaborative Activites
Team 15 – Deep Learning Handwriting Recognition
Team Members:
Baron Davis
Creighton Young
Micheal Oyenekan
William Farris
Project Summary:
The problem to solve is to improve an open-source handwriting recognition model. The overall objective is to improve the already 75% accuracy to a 90% accuracy with several avenues to continue forward. As time goes on, scanning documents for information will get increasingly more important as copying or translating written information to a machine-readable state takes time and money to do. For this reason, it is important for a program to exist that scans documents for letters and words and converts them to a far more readable and easy-to-store state for computers so that chronicling information is faster for people who need to record information but cannot bring devices with them to do so.
Contact:
For more information, please contact
Nathaniel Zinda at nathaniel.zinda@cgi.com
Rishi Dhaka at fnu.rishidhaka@cgi.com
Project Proposal:
Project Proposal Slide:
Team 15 – Final Proposal Slide
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