Pure Mathematics for Theoretical Computer Science

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https://doi.org/10.54216/PMTCS

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Volume 4 , Issue 1 , PP: 16-21, 2024 | Cite this article as | XML | Html | PDF | Full Length Article

Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction

Sackineh Shamil Jasim 1 *

  • 1 Department of Statistics - College of Administration and Economics -University of Karbala-Iraq - (sackineh.sh@uokerbala.edu.iq)
  • Doi: https://doi.org/10.54216/PMTCS.040102

    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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    Cite This Article As :
    Shamil, Sackineh. Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction. Pure Mathematics for Theoretical Computer Science, vol. , no. , 2024, pp. 16-21. DOI: https://doi.org/10.54216/PMTCS.040102
    Shamil, S. (2024). Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction. Pure Mathematics for Theoretical Computer Science, (), 16-21. DOI: https://doi.org/10.54216/PMTCS.040102
    Shamil, Sackineh. Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction. Pure Mathematics for Theoretical Computer Science , no. (2024): 16-21. DOI: https://doi.org/10.54216/PMTCS.040102
    Shamil, S. (2024) . Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction. Pure Mathematics for Theoretical Computer Science , () , 16-21 . DOI: https://doi.org/10.54216/PMTCS.040102
    Shamil S. [2024]. Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction. Pure Mathematics for Theoretical Computer Science. (): 16-21. DOI: https://doi.org/10.54216/PMTCS.040102
    Shamil, S. "Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction," Pure Mathematics for Theoretical Computer Science, vol. , no. , pp. 16-21, 2024. DOI: https://doi.org/10.54216/PMTCS.040102