Handwritten Digit Recognition from Image Using Confusion Matrix

Recently, the creation of numerous machine learning, deep learning and computer vision algorithms has rendered hand- written visual identification by researchers highly important. I compare the results of some of the most used algorithms such as SVM , KNN & RFC, and CNN. In this article. CNN using Theano and Tensorflow for Keras. With these, I was able to reach 99.6% precision with CNN (Keras+Theano), opposed to 98.00% with SVM, 98.22% with KNN, and 97.77% with RFC.

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Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-05-22
DOI
https://doi.org/10.52783/jisem.v10i49s.9880
Primary Topic
Handwritten Text Recognition Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Handwritten Digit Recognition from Image Using Confusion Matrix

M Y Raghavendra
Journal of Information Systems Engineering & Management
Handwritten Text Recognition Techniques
article

Handwritten Digit Recognition from Image Using Confusion Matrix

M Y Raghavendra
article en

Abstract

Recently, the creation of numerous machine learning, deep learning and computer vision algorithms has rendered hand- written visual identification by researchers highly important. I compare the results of some of the most used algorithms such as SVM , KNN & RFC, and CNN. In this article. CNN using Theano and Tensorflow for Keras. With these, I was able to reach 99.6% precision with CNN (Keras+Theano), opposed to 98.00% with SVM, 98.22% with KNN, and 97.77% with RFC.

Journal of Information Systems Engineering & ManagementVol. 10(49s)
Openalex Percentile: Top 90%
Handwritten Text Recognition Techniques
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Handwritten Digit Recognition from Image Using Confusion Matrix — M Y Raghavendra · Journal of Information Systems Engineering & Management (2025) | TGRS Research Map | TGRS