Research by Jim Samuel et al. “Customized AI Readers: An Adaptive Framework for Flexible Human Handwriting Recognition of Numerical Digits with OCR Methods”

June 16, 2023


Advanced artificial intelligence (AI) techniques have led to significant developments in optical character recognition (OCR) technologies. OCR applications, using AI techniques for transforming images of typed text, handwritten text, or other forms of text into machine-encoded text, provide a fair degree of accuracy for general text. However, even after decades of intensive research, creating OCR with human-like abilities has remained evasive. One of the challenges has been that OCR models trained on general text do not perform well on localized or personalized handwritten text due to differences in the writing style of alphabets and digits. This study aims to discuss the steps needed to create an adaptive framework for OCR models, with the intent of exploring a reasonable method to customize an OCR solution for a unique dataset of English language numerical digits were developed for this study. We develop a digit recognizer by training our model on the MNIST dataset with a convolutional neural network and contrast it with multiple models trained on combinations of the MNIST and custom digits. Using our methods, we observed results comparable with the baseline and provided recommendations for improving OCR accuracy for localized or personalized handwritten text. This study also provides an alternative perspective to generating data using conventional methods, which can serve as a gold standard for custom data augmentation to help address the challenges of scarce data and data imbalance.


OCR; adaptive; custom; digits; MNIST; informatics; machine learning; deep learning


Jain, P.H.; Kumar, V.; Samuel, J.; Singh, S.; Mannepalli, A.; Anderson, R. Customized AI Readers: An Adaptive Framework for Flexible Human Handwriting Recognition of Numerical Digits with OCR Methods. Information202314, 305.

Recent Posts

Sophia Jones, Committed to Cultural Competence

Sophia Jones, PhD, has been a Public Health part-time lecturer at the Bloustein School since 2016. She was recently featured on "Meet the People of Rutgers." Sophia Jones, Committed to Cultural Competence Jeff Arban/Rutgers University The Basics Title: Program...

NJSPL – New Jersey Employment Concerns Revisited

As 2024 began with yet another surprisingly strong jobs report for the U.S. (353,000 jobs added in January and the unemployment rate steady at 3.7%), and with a full year’s worth of 2023 state-level employment data now available, it’s worth briefly revisiting some of...

Upcoming Events

Lunch and Learn: Health and Housing Equity Cluster

Bloustein School, Civic Square Building 33 Livingston Avenue, New Brunswick, NJ, United States

The Rutgers Housing & Health Equity Cluster would like to invite you to join us for an in-person lunch and learn. All are welcome to bring lunch and eat during […]