LeeJunHyun/Image_Segmentation
PyTorch implementations of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net for biomedical image segmentation.
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This repository provides PyTorch implementations of four convolutional neural network architectures for image segmentation. The models include standard U-Net, recurrent residual U-Net (R2U-Net), attention U-Net, and their combined variant (Attention R2U-Net). Evaluations were conducted on the ISIC 2018 skin lesion segmentation dataset.
Frequently asked
- What is LeeJunHyun/Image_Segmentation?
- PyTorch implementations of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net for biomedical image segmentation.
- Is Image_Segmentation open source?
- Yes — LeeJunHyun/Image_Segmentation is an open-source project tracked on heatdrop.
- What language is Image_Segmentation written in?
- LeeJunHyun/Image_Segmentation is primarily written in Python.
- How popular is Image_Segmentation?
- LeeJunHyun/Image_Segmentation has 3.1k stars on GitHub.
- Where can I find Image_Segmentation?
- LeeJunHyun/Image_Segmentation is on GitHub at https://github.com/LeeJunHyun/Image_Segmentation.