TY - JOUR AU - Guevara Neri, Cristina AU - Vergara Villegas, Osslan Osiris AU - Cruz Sánchez, Vianey Guadalupe AU - Nandayapa, Manuel AU - Sossa Azuela, Juan Humberto PY - 2020/01/01 Y2 - 2024/03/28 TI - A Convolutional Neural Network for Handwritten Digit Recognition JF - International Journal of Combinatorial Optimization Problems and Informatics JA - Int. Journal of COP and Infor. VL - 11 IS - 1 SE - Articles DO - UR - https://ijcopi.org/ojs/article/view/163 SP - 97-105 AB - <p>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.</p> ER -