I want to ask the dimension change in different convolution and max-pooling layer. I am referring to the example in TensorFlow tutorial:
http://tensorflow.org/tutorials/mnist/pros/index.html#deep-mnist-for-experts
The original image is a 28x28x1
The first convolutional layer:
- apply convolution to a 5x5 patch with 32 features -> 24x24x32
- apply max-pooling 2x2 -> 12x12x32
Second convolutional layer:
- apply convolution to a 5x5 patch with 64 features -> 8x8x64
- apply max-pooling 2x2 -> 4x4x64
But it said "Now that the image size has been reduced to 7x7" but my calculation seems to claim that it is a 4x4
Did I miss some concept? I am new to CNN so it may be a beginner question.
Thanks