For below line of code
model.add(Conv2D(filters = 32, kernel_size = (5,5),padding = 'Same',
activation ='relu', input_shape = (28,28,1)))
Here, what does 'filers' and 'kernel_size' mean? or what is filter and kernel_size ?
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$\begingroup$ Please refer older answers stackoverflow.com/questions/34831038/… $\endgroup$– thanatozApr 3, 2019 at 13:14
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1$\begingroup$ Possible duplicate of Why do convolutional neural networks work? $\endgroup$– thanatozApr 3, 2019 at 13:15
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1 Answer
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Filters are used to extract features from images in the process of convolution.
filters: Integer, the dimensionality of the output space (i.e. the number of output filters in the convolution).
kernel_size: An integer or tuple/list of 2 integers, specifying the height and width of the 2D convolution window. Can be a single integer to specify the same value for all spatial dimensions.
For detailed undestadning of filter and kernel_size, refer:
https://www.saama.com/blog/different-kinds-convolutional-filters/
https://keras.io/layers/convolutional/
