EMERGING TRENDS IN COMPUTING
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Suppose you have 5 convolutional kernel of size 7 x 7 with zero padding and stride 1 in the first layer of a convolutional neural network. You pass an input of dimension 224 x 224 x 3 through this layer. What are the dimensions of the data which the next layer will receive?
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217 x 217 x 3
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217 x 217 x 8
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218 x 218 x 5
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220 x 220 x 7 Suppose you have 5 convolutional kernel of size 7 x 7 with zero padding and stride 1 in the first layer of a convolutional neural network. You pass an input of dimension 224 x 224 x 3 through this layer. What are the dimensions of the data which the next layer will receive?
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Explanation:
Detailed explanation-1: -In the simple case, the size of the output CNN layer is calculated as “input size-(filter size-1)”. For example, if the input image size is (50, 50) and filter is (3, 3) then (50-(3–1)) = 48. But the size of the input image of a Convolutional network should not be less than the input, so padding is done.
Detailed explanation-2: -Horizontal padding The formula given for calculating the output size (one dimension) of a convolution is (W−F+2P)/S+1. You can reason it in this way: when you add padding to the input and subtract the filter size, you get the number of neurons before the last location where the filter is applied.
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