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Journal of Artificial Intelligence and Metaheuristics
Volume 6 , Issue 1, PP: 18-26 , 2023 | Cite this article as | XML | Html |PDF

Title

Optical Character Recognition System for Digit Recognition Using Deep Learning

  Mona Awad 1 * ,   Marwa M. Eid 2

1  Delta Higher Institute of Engineering and Technology, Mansoura 35111, Egypt
    (Dr.mona711@gmail.com)

2  Faculty of Artiļ¬cial Intelligence, Delta University for Science and Technology, Mansoura 11152, Egypt
    (mmm@ieee.org)


Doi   :   https://doi.org/10.54216/JAIM.060102

Received: February 09, 2023 Revised: May 17, 2023 Accepted: November 15, 2023

Abstract :

Because it is so difficult to distinguish handwritten digits, digit identification is one of the most critical applications in computer vision. This is one of the reasons why it is so tough. The field of handwritten character recognition is one in which a great deal of application of numerous deep learning models has occurred. The startling parallels that can be drawn between deep learning and the brain are primarily responsible for its meteoric rise in popularity. In this study, the Artificial Neural Network and the Convolutional Neural Network, two of the most used Deep Learning algorithms, were investigated with an eye toward the recognition process's feature extraction and classification phases. With the assistance of the categorical cross-entropy loss and the ADAM optimizer, the models were trained on the MNIST dataset. Backpropagation and gradient descent are the two methods utilized during the training process of neural networks that contain reLU activations and carry out automatic feature extraction. In computer vision, one of the most common and widely used classifiers is the Convolution Neural Network, sometimes referred to as ConvNets or Convolutional neural networks. This network is used for the recognition and categorization of images.

Keywords :

OCR; AI; Neural Network.

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Cite this Article as :
Style #
MLA Mona Awad, Marwa M. Eid. "Optical Character Recognition System for Digit Recognition Using Deep Learning." Journal of Artificial Intelligence and Metaheuristics, Vol. 6, No. 1, 2023 ,PP. 18-26 (Doi   :  https://doi.org/10.54216/JAIM.060102)
APA Mona Awad, Marwa M. Eid. (2023). Optical Character Recognition System for Digit Recognition Using Deep Learning. Journal of Journal of Artificial Intelligence and Metaheuristics, 6 ( 1 ), 18-26 (Doi   :  https://doi.org/10.54216/JAIM.060102)
Chicago Mona Awad, Marwa M. Eid. "Optical Character Recognition System for Digit Recognition Using Deep Learning." Journal of Journal of Artificial Intelligence and Metaheuristics, 6 no. 1 (2023): 18-26 (Doi   :  https://doi.org/10.54216/JAIM.060102)
Harvard Mona Awad, Marwa M. Eid. (2023). Optical Character Recognition System for Digit Recognition Using Deep Learning. Journal of Journal of Artificial Intelligence and Metaheuristics, 6 ( 1 ), 18-26 (Doi   :  https://doi.org/10.54216/JAIM.060102)
Vancouver Mona Awad, Marwa M. Eid. Optical Character Recognition System for Digit Recognition Using Deep Learning. Journal of Journal of Artificial Intelligence and Metaheuristics, (2023); 6 ( 1 ): 18-26 (Doi   :  https://doi.org/10.54216/JAIM.060102)
IEEE Mona Awad, Marwa M. Eid, Optical Character Recognition System for Digit Recognition Using Deep Learning, Journal of Journal of Artificial Intelligence and Metaheuristics, Vol. 6 , No. 1 , (2023) : 18-26 (Doi   :  https://doi.org/10.54216/JAIM.060102)