[BOOK] CNN KERNEL: Performance analysis based on kernel size of Convolutional Layers in a network
Published: 20 August 2021| Version 1 | DOI: 10.17632/f2chpmphn7.1
Al Mahmud Al Mamun
In this book, I perform an experimental review on twelve similar types of Convolutional Neural Network architecture but the different sizes of kernels for the filters. For this experiment, I select twelve different sizes of the kernel for twelve Convolutional Neural Network models, the size of kernels are – (12, 12), (11, 11), (10, 10), (9, 9), (8, 8), (7, 7), (6, 6), (5, 5), (4, 4), (3, 3), (2, 2), and (1, 1). The goal of this experiment is to help the developer to understand and select the perfect size of the kernel for filter during two-dimensional image processing by using the two-dimensional Convolutional (Conv2D) layer of CNNs.