Handwritten digit recognition has remained a topic of interest to computer vision scientists. Its origination precedes the emergence machine as it is crucial component digital transformation majority institutions in numerous fields. With uprising models, choosing satisfactory and fit algorithm for this multi-class (0-9) classification problem became challenging. This paper aims compare seven le...

This paper discusses a probabilistic on-line handwriting recognition scheme, based on Hidden Markov Models (HMM's), and its implementation for recognizing handwritten words captured from a tablet. Statistical methods, such as HMM's have been used successfully for speech recognition. These methods have recently been applied to the problem of handwriting recognition as well. This paper, discusses...

Introduction/purpose: This paper provides a survey of handwritten digit recognition methods tested on the MNIST dataset. Methods: The analyzes, synthesizes and compares development different classifiers applied to problem, from linear convolutional neural networks. Results: Handwritten classification accuracy dataset while using training testing sets is now higher than 99.5% most successful met...