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I have few question regarding CNN. In the figure below between Layer S2 and C3, 5*5 sized kernel has been used.enter image description here

Q1. How many kernel has been used there? Do each of these kernel connected with each of the feature map in Layer S2 ?

Q2. When using Max-pooling, while backpropageting error how a max-pooling feature/neuron knows/determines from which (feature map/neuron) in its previous immediate layer it got the max value ?

Q3. If we want to train kernel then we initialize with random value, is there any equation to update these kernel values using backpropagated error value ?

Q4. In the above figure how the backpropagation works between 'Input' and 'C5' layer after getting error from Layer F6 ?

Cœur
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Avijoy Chakma
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1 Answers1

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Q1: C1 -> 6 Kernels C3 -> 16 Kernels

S2 and S4 are just subsampling, this means 2*2 Pixel will be decreased to 1 Pixel The most populare Pooling Mechanism is the MAX Pooling:

 (  5   10 ) -->
 (         ) -->  (10)
 (  7    8 ) -->

Q2: You can save the information or if you have enough time re-run the max_pooling and check where the maximum is and then put the error at this position. The other values in this 2*2 Block are zero

JoJa
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