Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction

aspg-40-2915-1792469442 20261020041042 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Pure Mathematics for Theoretical Computer Science PMTCS 2995-3162 2024 4 1 Incorporating Kernels into Convolutional Neural Networks for Enhanced Feature Extraction Sackineh Shamil Jasim Department of Statistics - College of Administration and Economics -University of Karbala-Iraq 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. 2024 07 11 2915 https://creativecommons.org/licenses/by/4.0/ 10.54216/PMTCS.040102 https://www.americaspg.com/journal/40/article/2915 https://www.americaspg.com/storage/articles/manuscripts/01M1305XYMYTYB3QER4T8NPFNV.pdf