Comments (1)
You can add the transposed layers as a regularization method, or leave the network to learn entirely new filters. That is up to you and worth exploring both options to see how it effects the result! Good luck!
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Related Issues (20)
- Environment Setup: "docker: invalid reference format: repository name must be lowercase."
- The function `imcrop_tosquare` in session-0 has a minor problem
- Docker build failing HOT 2
- link to windows install resouce broken in readme
- Docker-gpu dockerfile build issue HOT 2
- Session 3's audio classification network should use internal tf cross entropy calculation
- Session 5; provided pre-trained model incompatible (and not loaded) HOT 6
- Number of epochs unused in dataset_utils.create_input_pipeline HOT 1
- 2 out of tree test failed from CADL-master\session-3\libs\vae.py HOT 2
- Checkpoint restoration for VAEGAN needs to account for global step
- `resize` should be `np.resize` for non ipython users
- Small potential error HOT 1
- tensorflow 1.4 with cuda8 or 9 ! HOT 1
- Lecture 5: ValueError: Only call `sparse_softmax_cross_entropy_with_logits` with named arguments (labels=..., logits=..., ...)
- lecture 4 : isn't there an issue with h,w ; in cell 31 ? HOT 2
- Windows 10 Path issues HOT 1
- Issue evaluating VGG16 model
- Session 2 typo: intializer => initializer
- Does this course contains nlp tasks with tensorflow?
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