In order to create a blur, one would need to execute a convolution between the kernel and an image.
<h3>What is a convolution?</h3>
Convolution describes both the outcome function and the technique of computing it.
It is defined as the product of two functions that have been reversed and shifted. The integral is computed for all shift values, yielding the convolution function.
Convolutions combine all of the pixels in their receptive area into a single value.
For example, if you apply a convolution to a picture, you will reduce the image size while also combining all of the information in the field into a single pixel.
The convolutional layer's final output is a vector.
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