Handwritten Digit Recognition Using Machine Learning

Rabia KARAKAYA; Serap KAZAN

doi:https://doi.org/10.16984/saufenbilder.801684

Makale detayları

Handwritten Digit Recognition Using Machine Learning

Yazarlar:

Rabia KARAKAYA | Serap KAZAN

Ana Başlıklar:

Özel bilgisayar yöntemleri

Dergi:

Sakarya University Journal of Science 2021 Vol.25 Issue 1, pp.65-71

Belge Tipi:

Makale

Yayın Tarihi:

1/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000556479

DOI:

https://doi.org/10.16984/saufenbilder.801684

Özet:

 

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 (SVM), Decision Tree, Random Forest, Artificial Neural Networks (ANN), K-Nearest Neighbor (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.

Makale detayları

Handwritten Digit Recognition Using Machine Learning

Yazarlar: Rabia KARAKAYA | Serap KAZAN

Ana Başlıklar: Özel bilgisayar yöntemleri

Dergi: Sakarya University Journal of Science 2021 Vol.25 Issue 1, pp.65-71

Belge Tipi: Makale

Yayın Tarihi: 1/2021

Belge Dili: İngilizce

Document ID (Org No.): 2000556479

DOI: https://doi.org/10.16984/saufenbilder.801684

Sayı

Yazarlar:

Rabia KARAKAYA | Serap KAZAN

Ana Başlıklar:

Özel bilgisayar yöntemleri

Dergi:

Sakarya University Journal of Science 2021 Vol.25 Issue 1, pp.65-71

Belge Tipi:

Makale

Yayın Tarihi:

1/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000556479

DOI:

https://doi.org/10.16984/saufenbilder.801684