Deep Morphological Gradient for Recognition of Handwritten Digits-Reference-Cited by-同舟云学术

Deep Morphological Gradient for Recognition of Handwritten Digits

Published:2019-10-23 Issue: Volume: Page:
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Container-title:Proceedings of the 4th International Conference on Big Data and Internet of Things
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Author:

El Atillah Mouhssine¹,El fazazy Khalid²

Affiliation:

1. Research team Complex Systems and Interactions, Ait Melloul, Agadir, Morocco

2. Research team Complex Systems and Interactions, Ait Melloul Agadir, Morocco

Publisher

ACM

Reference14 articles.

1. La reconnaissance optique de caract_eres (OCR) doit acc_el_erer sa disruption et _elargir son champ d'application, Economie Matin;Karim Jouini;Accessed,2019

2. A Comprehensive Survey;Srihari R. Plamondon;IEEE Transactions on Pattern Analysis and Machine Intelligence,2000

3. Springer-Verlag London Springer-Verlag A. Ouwayed N. Guide to OCR for Arabic Volker M· argner and Haikal El Abed 2011 103 122

4. July 2017 July 2017 6 AashiDutt Anuj Dutt Handwritten Digit Recognition Using Deep Learning. Issue 7 s.l.: International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)

5. The MNIST dataset provided in a easy-to-use CSV format. Kaggle https://www.kaggle.com/oddrationale/mnist-in-csv. The MNIST dataset provided in a easy-to-use CSV format. Kaggle https://www.kaggle.com/oddrationale/mnist-in-csv.

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