Project-MONAI / Project-MONAI/tutorials
3D classification example based on DenseNet - Occlusion Sensitivity
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- Dominant language
- Jupyter Notebook
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Description
Hi all,
I tried downloading and running the 3D classification example based on DenseNet tutorial code on occlusion sensitivity, but unfortunately it didn't generate the same map as the example for me.
This is what I've got so far.
Any ideas?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Download and run the 3D classification example based on DenseNet, then compare its occlusion-sensitivity map with the example image attached to the issue. Reproduce the mismatch and determine what needs to change so the generated map matches the tutorial result.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, pytorch
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100