unet
importedsoftware/unet
"pip install unet": PyTorch Implementation of 1D, 2D and 3D U-Net architecture.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/fepegar/unet
- Documentation
- unknown
- Tags
- convolutional-neural-networks · deep-learning · medical-imaging · unet · unet-image-segmentation · unet-pytorch
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- SelfReg-UNetmedical-imaging · unet · unet-image-segmentation
Code for the paper "SelfReg-UNet: Self-Regularized UNet for Medical Image Segmentation "
- UNeXt-pytorchmedical-imaging · unet · unet-image-segmentation
Official Pytorch Code base for "UNeXt: MLP-based Rapid Medical Image Segmentation Network", MICCAI 2022
- Mobile-U-ViTunet · unet-pytorch
[ACM MM 2025] Mobile U-ViT: Revisiting large kernel and U-shaped ViT for efficient medical image segmentation
- Retinal-vessel-segmentationunet · unet-pytorch
:tada:一个基于 UNet 的视网膜血管分割项目，使用 PyTorch 实现并基于 DRIVE 数据集进行训练和测试。项目包括完整的数据处理、模型训练和测试流程，最终生成视网膜图像的分割结果。
- teeth_segmentationmedical-imaging · unet-image-segmentation
teeth segmentation using UNet and customize attention module
- ACC-UNetmedical-imaging · unet
ACC-UNet is A Completely Convolutional UNet model inspired from transformer-based UNets
- api.github.com/repos/fepegar/unetretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2024-12-13, 200 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/27.json→ .entries["unet"]
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