APPLICATION OF SUPERVISED LEARNING
DEEP LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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In CNN’s which of the following layers exploits spatial locality of input data?
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Fully connected layer
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Input layer
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Convolution layer
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Max pooling layer
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Explanation:
Detailed explanation-1: -CNN has one or more layers of convolution units, which receives its input from multiple units. CNN uses a more simpler alghorithm than ANN. CNN is a easiest way to use Neural Networks. They complete eachother, so in order to use ANN, you need to start with CNN.
Detailed explanation-2: -Pooling or spatial pooling layers: Also called subsampling or downsampling. It is applied after convolution and RELU operations. It reduces the dimensionality of each feature map by retaining the most important information.
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