Handwritten Digit Recognition Using Machine Learning

Authors : Rabia KARAKAYA, Serap KAZAN

Pages : 65-71

Doi:10.16984/saufenbilder.801684

View : 14 | Download : 8

Publication Date : 2021-02-01

Article Type : Research Paper

Abstract :Technology is getting more and more involved in our lives, and so are algorithms. These algorithms speed up work and reduce workload. Especially machine learning algorithms are improving day by day by imitating human behaviours. Handwriting recognition systems are also stand out on this field. In this study, handwriting digit recognition process has been done with algorithms having different working methods. These algorithms are Support Vector Machine insert ignore into journalissuearticles values(SVM);, Decision Tree, Random Forest, Artificial Neural Networks insert ignore into journalissuearticles values(ANN);, K-Nearest Neighbor insert ignore into journalissuearticles values(KNN); and K- Means Algorithm. The working logic of the handwriting digit recognition process was examined, and the efficiency of different algorithms on the same database was measured. A report was presented by making comparisons on the accuracy.
Keywords : handwritten digit recognition, machine learning, artificial intelligence