Analysis of machine learning algorithms for character recognition: a case study on handwritten digit recognition

Owais Mujtaba Khandy (University of Miskolc)
Samad Dadvandipour (University of Miskolc)

Indonesian Journal of Electrical Engineering and Computer Science
Vol 21, No 1: January 2021

This paper covers the work done in handwritten digit recognition and the various classifiers that have been developed. Methods like MLP, SVM, Bayesian networks, and random forests were discussed with their accuracy and are empirically evaluated. Boosted LetNet 4, an ensemble of various classifiers, has shown maximum efficiency among these methods.