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I'm studying for a computer vision module and I'm on the deep learning topic, in one past paper we have the following question:

Given that a convolutional neural network has five convolution layers (all the convolution layers are composed of 3×3 convolution filters with stride 1 and no pooling layers), calculate how many pixel(s) in the input image are supporting a neuron in the fifth layer?

without the input size of the image, how is it possible to work this out?

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If there is only one convolution layer, then every neuron is supported by $3 \times 3 = 9$ pixels in the input image. This doesn't depend on the size of the image. You can generalize this to more layers.

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  • $\begingroup$ Ok, that makes sense thank you! So we would take the number of layers * the number of pixels supported by the first layer, given all the layers in the network are convolutional layers? is this correct or would we do the number of pixels to the power of the number of layers? $\endgroup$
    – Yallooss
    Jun 2 at 12:34
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    $\begingroup$ I think you now have enough information to solve the problem on your own. $\endgroup$ Jun 2 at 12:35

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