(untitled) (European Journal of Pure and Applied Mathematics, 2025)
In convolutional neural networks (CNN), the problem of heat generation is becoming a significant issue. This challenge can be mitigated through both hardware and software methods. This study focuses on drastically reducing the amount of computations and, consequently, the heat generation. Specifically, the proposed approach reduces computations by approximately m × 2^n, where m is the number of layers and n is the size of the node.