Pinned Repositories
2D-liver-jpg-gif-Segmentation
gif jpg hd dice miou segmentation
3DUnet-Tensorflow-Brats18
3D Unet biomedical segmentation model powered by tensorpack with fast io speed
Brain-tumor-detection-in-3D-MRIs-using-DCGAN
Using DCGAN for segmenting brain tumors from brain image scans
Brain-tumor-segmentation
A deep learning based approach for brain tumor MRI segmentation.
Brain_generate
Brain_Tumour_Segmentation
Code for training a 3DUnet for Brain tumour segmentation from Brats 2019 dataset; for feature extraction from the segmented volumes and for survival prediction. Run train.py for training, segment.py for segmenting test scans and evaluate.py for evaluating the performance of those segmentations. Basic code also written to perform survival prediction with a random forest classifiier.
cifar10
DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
DenseUNet-pytorch
A Pytorch implementation of U-Net using a DenseNet-121 backbone
two-stage-VAE-Attention-gate-BraTS2020
A Two-Stage Cascade Model with Variational Autoencoders and Attention Gates for MRI Brain Tumor Segmentation (BraTS 2020 Challenge; BrainLes2020 paper)
zhangshuang317's Repositories
zhangshuang317/2D-liver-jpg-gif-Segmentation
gif jpg hd dice miou segmentation
zhangshuang317/two-stage-VAE-Attention-gate-BraTS2020
A Two-Stage Cascade Model with Variational Autoencoders and Attention Gates for MRI Brain Tumor Segmentation (BraTS 2020 Challenge; BrainLes2020 paper)
zhangshuang317/3DUnet-Tensorflow-Brats18
3D Unet biomedical segmentation model powered by tensorpack with fast io speed
zhangshuang317/Brain-tumor-detection-in-3D-MRIs-using-DCGAN
Using DCGAN for segmenting brain tumors from brain image scans
zhangshuang317/Brain-tumor-segmentation
A deep learning based approach for brain tumor MRI segmentation.
zhangshuang317/Brain_generate
zhangshuang317/Brain_Tumour_Segmentation
Code for training a 3DUnet for Brain tumour segmentation from Brats 2019 dataset; for feature extraction from the segmented volumes and for survival prediction. Run train.py for training, segment.py for segmenting test scans and evaluate.py for evaluating the performance of those segmentations. Basic code also written to perform survival prediction with a random forest classifiier.
zhangshuang317/cifar10
zhangshuang317/DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
zhangshuang317/DenseUNet-pytorch
A Pytorch implementation of U-Net using a DenseNet-121 backbone
zhangshuang317/DOPE.pytorch
DOPE (Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects)
zhangshuang317/kits19-challenge
Kidney Tumor Segmentation Challenge 2019
zhangshuang317/Librarys
djiango-Librarys python图书管理系统
zhangshuang317/pytorch-3dunet
3D U-Net model for volumetric semantic segmentation written in pytorch
zhangshuang317/pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch
zhangshuang317/Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
zhangshuang317/RAGAN
zhangshuang317/unet
unet for image segmentation