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.
handwritten digit recognition machine learning artificial intelligence
Birincil Dil | İngilizce |
---|---|
Konular | Yapay Zeka |
Bölüm | Araştırma Makalesi |
Yazarlar | |
Yayımlanma Tarihi | 1 Şubat 2021 |
Gönderilme Tarihi | 29 Eylül 2020 |
Kabul Tarihi | 30 Ekim 2020 |
Yayımlandığı Sayı | Yıl 2021 Cilt: 25 Sayı: 1 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.