Alright, let's do this! Okay, I've crunched the numbers, and I'm pretty sure the answer is 8*8. Although, I have to admit, I'm a little disappointed that none of the options include 7*7. That would have really thrown me for a loop!
Hah, this question is a real brainteaser! I'm gonna have to go with 8*8 on this one. After all, who wants to be the sucker that picks 10*10 and gets it wrong? Not this guy, that's for sure. Although, if I'm being honest, I'm kind of hoping someone else goes with 4*4 just so I can have a good laugh.
I'm going with option C, 8*8. The math checks out, and it makes the most sense given the information provided. Though, I have to say, the person who wrote this question must have been feeling a bit cheeky. 10*10? Really? What is this, amateur hour?
Hmm, let me think about this. The input image is 28*28, and the first convolutional layer has 6 filters of size 5*5 with a stride of 1, which should give us a 24*24 feature map. Then, the max pooling layer with a 2*2 window and stride of 2 should give us a 12*12 output. Not sure why the question mentions 10*10, though.
I think the output tensor size is 8*8. The max pooling layer with a 2x2 window and stride of 2 should reduce the spatial dimensions by half, resulting in an 8*8 output.
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