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About kernel size for Down Conv and Up Conv layers #15

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rtgunti opened this issue Jun 6, 2020 · 1 comment
Open

About kernel size for Down Conv and Up Conv layers #15

rtgunti opened this issue Jun 6, 2020 · 1 comment

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@rtgunti
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rtgunti commented Jun 6, 2020

Hi, thanks for the great repo. The 'Visual Representation' shows that kernel size used for Down Conv and Up Conv layers used is (2x2x1). However, it's (2x2x2) in the code. The latter one makes sense though. Could you please let me know if it's a typo in the figure?

@jackyko1991
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The figure is inherited from the repo https://github.com/MiguelMonteiro/VNet-Tensorflow

After checking with original paper: https://arxiv.org/pdf/1606.04797.pdf

This is performed through convolution with 2 × 2 × 2 voxels wide kernels applied with stride 2.

The code should be correct one and there is typo in the graph

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