Convolutional Neural Network (CNN) Layer Development for Effectiveness of Classification Tasks


  • Rafayel M. Veziryan Institute for Informatics and Automation Problems of NAS RA
  • Rafayel N. Khachatryan Questrade Armenia Inc.



DCNN, Classification task, Image processing, ResNet, PDE, Cable equation, Grid method


This paper presents a novel 2D convolutional layer motivated by the principles of Partial Differential Equation (PDE) of Neural Interaction. Our objective is to leverage this layer to enhance the classification accuracy of Deep Convolutional Neural Networks (DCNN) for various classification tasks. We place a particular emphasis on its integration within the ResNet architecture, and we conduct experimental evaluations on the CIFAR10 and STL10 datasets to validate its efficacy.


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How to Cite

Veziryan, R. M., & Khachatryan, R. N. (2023). Convolutional Neural Network (CNN) Layer Development for Effectiveness of Classification Tasks. Mathematical Problems of Computer Science, 60, 63–71.