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slmatrix avatar slmatrix commented on May 17, 2024

(..) provided that the parameters of the fully connected network (..)

should say layer.

from a-pytorch-tutorial-to-object-detection.

slmatrix avatar slmatrix commented on May 17, 2024

conv6 will use 1024 filters, each with dimensions 1, 1, 1024

should say conv7 and dimensions should be 2, 2, 1024 because previous layer is decimated to 3, 3, 512?

from a-pytorch-tutorial-to-object-detection.

AnhPC03 avatar AnhPC03 commented on May 17, 2024

@slmatrix FM10 is 3x3(x256), why FM11 is 1x1(x256)? I think it should be 2x2(x256) because use 2x2 max pooling, and use the mathematical ceiling function.

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slmatrix avatar slmatrix commented on May 17, 2024

@AnhPC03, there is no max pooling. The auxiliary layers downsample their spatial dims by convolutions with zero padding (side effect of convolution is downsampling which is why padding is typically done in conv layers).

Closing this issue.

from a-pytorch-tutorial-to-object-detection.

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