Cooperative_Training_and_Latent_Space_Data_Augmentation
importedsoftware/cooperative-training-and-latent-space-data-augmentation
[MICCAI 2021 Oral] Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- Apache-2.0, MIT(mixed)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Documentation
- unknown
- Tags
- image-segmentation · medical-imaging · segmentation · single-domain-generalization
- Regulatory
- unknown
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- federated_heimage-segmentation · medical-imaging · segmentation
Federated learning with homomorphic encryption enables multiple parties to securely co-train artificial intelligence models in pathology and radiology, reaching state-of-the-art performance with…
- MedSegDiffimage-segmentation · medical-imaging · segmentation
Using Diffusion Models to Segment/Reconstruct Organs from Medical Images [AAAI Most influential Paper]
- VNetimage-segmentation · medical-imaging · segmentation
Prostate MR Image Segmentation 2012
- VNet3Dimage-segmentation · medical-imaging · segmentation
Prostate MR Image Segmentation 2012
- GeoLSimage-segmentation · segmentation
Adding Image-context in the Label Smoothing process via Geodesic distance
- pansegimage-segmentation · segmentation
A tool for cell instance aware segmentation in densely packed 3D volumetric images
- api.github.com/repos/cherise215/Cooperative_Training_and_Latent_Space_Data_Augmentationretrieved 2026-08-25 · via github-api
Machine-imported from GitHub search. Last push 2021-12-06, 36 stars, license reported as NOASSERTION. Category and schematic were assigned by keyword heuristics and are unreviewed. GitHub reported NOASSERTION; the licence was read from the LICENSE file as Apache-2.0, MIT, because GitHub's detector does not recognise open hardware licences.
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