Analysis of machine learning algorithms for character recognition: a case study on handwritten digit recognition
2021 ◽
Vol 21
(1)
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pp. 574
Keyword(s):
<p><span>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. </span></p>
2018 ◽
Vol 3
(1)
◽
pp. 29
◽
Keyword(s):
2018 ◽
Vol 06
(05)
◽
pp. 96-100
Keyword(s):