91一级特黄大片|婷婷中文字幕在线|av成人无码国产|日韩无码一二三区|久久不射强奸视频|九九九久久久精品|国产免费浮力限制

圖像分割領(lǐng)域常用網(wǎng)站
來(lái)源: 方江雄/
臺(tái)州學(xué)院
1295
0
0
2024-02-15

1.  semantic segmentation frameworks 

https://github.com/SegmentationBLWX/sssegmentation

 

2. instance segmentation algorithm 

https://github.com/LiWentomng/boxlevelset

https://github.com/LiWentomng/Box-supervised-instance-segmentation

https://github.com/facebookresearch/maskrcnn-benchmark

https://zhuanlan.zhihu.com/p/390340434

https://zhuanlan.zhihu.com/p/607593361

https://zhuanlan.zhihu.com/p/607624400

 

3. Semi-supervised-learning segmentation

https://github.com/HiLab-git/SSL4MIS

https://github.com/Haochen-Wang409/U2PL

https://github.com/HiLab-git/DTC

https://github.com/googleinterns/wss

https://github.com/PengtaoJiang/Awesome-Weakly-Supervised-Semantic-Segmentation-Papers#2023

https://github.com/YudeWang/SSENet-pytorch

 

4. medical image segmentation

https://github.com/yhygao/CBIM-Medical-Image-Segmentation

https://github.com/Project-MONAI/MONAI/tree/dev/monai

 

5. multimodual medical image segmentation

https://github.com/black0017/MedicalZooPytorch

 

6. 3D medical image segmentation

https://github.com/black0017/MedicalZooPytorch/tree/master

 

7. UniverSeg: Universal Medical Image Segmentation 

https://github.com/JJGO/UniverSeg

 

8. Self-supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation

https://github.com/cheng-01037/Self-supervised-Fewshot-Medical-Image-Segmentation

 

9 Building-Detection-MaskRCNN

https://github.com/Mstfakts/Building-Detection-MaskRCNN

 

10. Adapting Segment Anything Model  

https://zhuanlan.zhihu.com/p/625171421

https://github.com/WuJunde/Medical-SAM-Adapter

https://github.com/bowang-lab/MedSAM

 

11.Weakly-supervised  segmentation Architecture

https://github.com/HiLab-git/WSL4MIS

 

12.仿照百度PaddleSeg結(jié)構(gòu)實(shí)現(xiàn)的一個(gè)醫(yī)學(xué)影像方向分割任務(wù)開發(fā)套件 

https://github.com/linhandev/medSeg

13. 可視化醫(yī)學(xué)圖像分割軟件

Active Learning with the nnUNet and Sample Selection with Uncertainty-Aware Submodular Mutual Information Measure (https://github.com/Kent0n-Li/Medical-Image-Segmentation)

 

 


登錄用戶可以查看和發(fā)表評(píng)論, 請(qǐng)前往  登錄 或  注冊(cè)。
SCHOLAT.com 學(xué)者網(wǎng)
免責(zé)聲明 | 關(guān)于我們 | 聯(lián)系我們
聯(lián)系我們: