Handwritten Digit Recognition by Deep Learning for Automatic Entering of Academic Transcripts-Reference-Cited by-同舟云学术

Handwritten Digit Recognition by Deep Learning for Automatic Entering of Academic Transcripts

Published:2020 Issue: Volume: Page:575-584
ISSN:2194-5357
Container-title:Software Engineering Perspectives in Intelligent Systems
language:
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Author:

Nouri Houssem Eddine

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-63319-6_53

Reference22 articles.

1. Alhajj, R., Elnagar, A.: Multiagents to separating handwritten connected digits. IEEE Trans. Syst. Man Cybern.-Part A Syst. Hum. 35(5), 593–602 (2005)

2. Aly, S., Mohamed, A.: Unknown-length handwritten numeral string recognition using cascade of PCA-SVMNet classifiers. IEEE Access 7(1), 52024–52034 (2019)

3. Cohen, G., Afshar, S., Tapson, J., Van Schaik, A.: EMNIST: an extension of MNIST to handwritten letters. Comput. Vis. Pattern Recogn. 1(1), 1–10 (2017)

4. Gangaputra, S.: Handwritten digit database (2013). http://cis.jhu.edu/~sachin/digit/digit.html

5. Ghosh, M.M.A., Maghari, A.Y.: A comparative study on handwriting digit recognition using neural networks. In: The International Conference on Promising Electronic Technologies, pp. 77–81 (2017)

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