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Convolutional Neural Networks

Convolutional Neural Networks

Understand the mathematical operation of convolution and discover the use of convolution to construct a convolutional neural network to function on discrete images.

What is a convolution?

Convolution is a linear mathematical operation that combines two signals or mathematical functions, f(x)f(x) and g(x)g(x), to produce an output signal, h(x)h(x). Mathematically:

The symbol * denotes a convolution operation, whereas the rightmost expression involving a summation is a convolution sum. Convolution is usually employed to find the output response h(x)h(x) against the input signal f(x)f(x) when passed through a kernel or a filter g(x)g(x).

Two-dimensional convolution

Digital images are two–dimensional signals that have two spatial independent variables: xx and yy ...