Comments (5)
@mg64ve --- good question. Unfortunately, my experience with both the squeeze-and-excite block as well as 1-D convolutional architectures are very limited. In fact, I haven't had a chance to test this yet. Since the 2-D case is
layer_permute( c( 4, 2, 3 ) )
and the 3-D case is
layer_permute( c( 5, 2, 3, 4 ) )
I suspect the 1-D case would be
layer_permute( c( 3, 2 ) )
but I'd have to do some more testing/thinking to be sure.
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Thanks @ntustison
It seems to work.
If I have time to document and add an example I will create a pull request, I guess it might be useful for someone else.
However now I would like to transform createResNetModel1D 1D ResNet CNN neural network model in an autoencoder.
Any good idea on how to make it?
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Sorry, I don't. We have a couple of autoencoder code snippets but I haven't translated any of them to 1-D.
from antsrnet.
Ok @ntustison , but do you have 2D or 3D resnet autoencoder?
from antsrnet.
No, we don't have that architecture implemented.
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Related Issues (20)
- Code error in the example for "createUnetModel2D" HOT 8
- 3D image dataset for a tutorial of image segmentation HOT 1
- Instructions for deepFlash and deepAtropos HOT 2
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- Remove unnecessary code? HOT 2
- Poor results in brainExtraction HOT 4
- Regarding 'desikanKillianyTourvilleLabeling' HOT 8
- Training with template base data augmentation HOT 5
- Cortical thickness: Error in atropos$probabilityImages[[4]] + atropos$probabilityimages[[5]] : HOT 2
- desikanKillianyTourvilleLabeling only produces few ROI stats HOT 1
- Huge memory usage after using desikanKillianyTourvilleLabeling() HOT 3
- Cortical thickness evaluation inconsistency!!! HOT 17
- Any possibility of refining DKT labels HOT 4
- Reference for DeepFlash HOT 1
- A 'tensorflow not found' error HOT 2
- Are ANTsRNet functions available for **training** and **testing** UNet models? HOT 5
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- Installation Issue. HOT 3
- Installation failed. HOT 4
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