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Pure Mathematics for Theoretical Computer Science

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Pure Mathematics for Theoretical Computer Science
Full Length Article

Volume 4Issue 1PP: 07–11 • 2024

Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction

Sackineh Shamil Jasim 1*
1Department of Statistics - College of Administration and Economics -University of Karbala-Iraq
* Corresponding Author.
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© 2024 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

Received: December 13, 2023 Revised: March 17, 2024 Accepted: May 24, 2024

Abstract

The simulation was used to evaluate the method of kernel K , Neural network NN, Convolution Neural network  CNN bys using (MINIST) data set. The accuracy of the method was tested and compared with the convolutional neural network as well as with the kernel function for the same input data (training and testing). The results of simulation showed that there is a high accuracy of the method, and at the same time there is a decreasing loss over the epochs, which indicates the. We note high smooth by method for recognize among features.

Keywords

Convolution MINIST kernel neural network convolution simulation

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Jasim, Sackineh Shamil. "Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction." Pure Mathematics for Theoretical Computer Science, vol. 4, no. 1, 2024, pp. 07–11. DOI: https://doi.org/10.54216/PMTCS.040102
Jasim, S. (2024). Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction. Pure Mathematics for Theoretical Computer Science, Volume 4(Issue 1), 07–11. DOI: https://doi.org/10.54216/PMTCS.040102
Jasim, Sackineh Shamil. "Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction." Pure Mathematics for Theoretical Computer Science Volume 4, no. Issue 1 (2024): 07–11. DOI: https://doi.org/10.54216/PMTCS.040102
Jasim, S. (2024) 'Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction', Pure Mathematics for Theoretical Computer Science, Volume 4(Issue 1), pp. 07–11. DOI: https://doi.org/10.54216/PMTCS.040102
Jasim S. Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction. Pure Mathematics for Theoretical Computer Science. 2024;Volume 4(Issue 1):07–11. DOI: https://doi.org/10.54216/PMTCS.040102
S. Jasim, "Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction," Pure Mathematics for Theoretical Computer Science, vol. Volume 4, no. Issue 1, pp. 07–11, 2024. DOI: https://doi.org/10.54216/PMTCS.040102
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