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For questions related to the convolution operation in mathematics, convolutional neural networks, image processing and computer vision.

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Is there anything that ensures that convolutional filters don't end up the same?

I trained a simple model to recognize handwritten numbers from the mnist dataset. Here it is: model = Sequential([ Conv2D(filters=1, kernel_size=(3,1), padding='valid', strides=1, input_shape=(28, …
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