A Convolutional Neural Network for Handwritten Digit Recognition

被引：1

作者：

Guevara Neri, Maria Cristina ^{[1
]}

Vergara Villegas, Osslan Osiris ^{[2
]}

Cruz Sanchez, Vianey Guadalupe ^{[2
]}

Nandayapa, Manuel ^{[2
]}

Sossa Azuela, Juan Humberto ^{[3
]}

机构：

[1] Univ Autonoma Ciudad Juarez, Inst Ingn & Tecnol, Ciencias Ingn DOCIA, Ciudad Juarez, Chihuahua, Mexico

[2] Univ Autonoma Ciudad Juarez, Inst Ingn & Tecnol, Ciudad Juarez, Chihuahua, Mexico

[3] IPN, CIC, Mexico City, DF, Mexico

来源：

INTERNATIONAL JOURNAL OF COMBINATORIAL OPTIMIZATION PROBLEMS AND INFORMATICS | 2020年 / 11卷 / 01期

关键词：

CNN; Digit Recognition; Image Preprocessing;

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Technological development in recent years has generated the constant need to digitalize and analyze data, where handwritten digit recognition is a popular problem. This paper focuses on the creation of two handwritten digit datasets and their use to train a Convolutional Neural Network (CNN) to classify them, also, a proposed extra preprocessing technique is applied to the images of one of the data sets. Experiments show that the proposed preprocessing technique lead to obtain accuracies above 98%, which were higher than the values obtained with the dataset without the additional preprocessing.

引用

页码：97 / 105

页数：9

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