A user-adaptive deep machine learning method for handwritten digit recognition

Abstract

The HWR (handwritten recognition) problem gains more attention with the development of machine learning. In this work, a user-adaptive HWR method is purposed for the application when only handwritten digits and few limited characters need to be recognized. Five types of CNN (Convolutional Neural Network) classifier are used in three steps: digits recognition, string-type classifier and string recognition. Experiment results show that the purposed method is capable of HWR for digits and few limited characters.