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In a CNN, if we have a 32x32x3 input volume followed by four layers of 3x3x3filters with stride = 1 and pad = 0, how many parameters must be learned?(a) 4(b) 27(c) 28(d) 108(e) 112

Question

In a CNN, if we have a 32x32x3 input volume followed by four layers of 3x3x3filters with stride = 1 and pad = 0, how many parameters must be learned?(a) 4(b) 27(c) 28(d) 108(e) 112

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Solution

In a Convolutional Neural Network (CNN), the number of parameters that must be learned is determined by the size of the filters and the number of filters used.

In this case, we have a 3x3x3 filter. Each filter has 333 = 27 weights. Additionally, each filter has 1 bias term. So, each filter has 27 + 1 = 28 parameters.

Since we have four layers of these filters, the total number of parameters to be learned is 4 * 28 = 112.

So, the answer is (e) 112.

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