negalotus

negalotus's Stars

• WenPai-org/wp-china-yes

  文派叶子 🍃（WP-China-Yes）是** WordPress 生态基础设施软件，犹如落叶新芽，生生不息。

  Language:PHP62871

• TrickyGo/Dive-into-DL-TensorFlow2.0

  本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现，项目已得到李沐老师的认可

  Language:Jupyter Notebook3.8k822

• ShusenTang/Dive-into-DL-PyTorch

  本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

  Language:Jupyter Notebook18.5k5.4k

• ralpguler/DenseReg

  Code repository for DenseReg.

  Language:Jupyter Notebook25474

• nndl/nndl.github.io

  《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning

  Language:HTML17.6k3.6k

• amueller/introduction_to_ml_with_python

  Notebooks and code for the book "Introduction to Machine Learning with Python"

  Language:Jupyter Notebook7.5k4.6k

• firmai/awesome-google-colab

  Google Colaboratory Notebooks and Repositories (by @firmai)

  Language:Jupyter Notebook1.4k258

• toxtli/awesome-machine-learning-jupyter-notebooks-for-colab

  A curated list of Machine Learning and Deep Learning tutorials in Jupyter Notebook format ready to run in Google Colaboratory

  Language:Jupyter Notebook29372

• firatozdemir/LwfSeg-AeiSeg

  Extending Pretrained Segmentation Networkswith Additional Anatomical Structures

  Language:Python72

• arnab39/FewShot_GAN-Unet3D

  Tensorflow implementation of our paper: Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning

  Language:Python38483

• xinario/awesome-gan-for-medical-imaging

  Awesome GAN for Medical Imaging

  2.3k460

• yuanxiaosc/DeepImage-an-Image-to-Image-technology

  DeepNude's algorithm and general image generation theory and practice research, including pix2pix, CycleGAN, UGATIT, DCGAN, SinGAN, ALAE, mGANprior, StarGAN-v2 and VAE models (TensorFlow2 implementation). DeepNude的算法以及通用生成对抗网络（GAN,Generative Adversarial Network）图像生成的理论与实践研究。

  Language:Python5.2k2k

• carrenD/Medical-Cross-Modality-Domain-Adaptation

  [IJCAI'18] Unsupervised Cross-Modality Domain Adaptation of ConvNets for Biomedical Image Segmentations with Adversarial Loss (code&data)

  Language:Python28558

• L1aoXingyu/code-of-learn-deep-learning-with-pytorch

  This is code of book "Learn Deep Learning with PyTorch"

  Language:Jupyter Notebook2.8k1.2k

• zhixinshu/DeformingAutoencoders-pytorch

  Pytorch code for DAE and IntrinsicDAE

  Language:Python12417

• fchollet/deep-learning-with-python-notebooks

  Jupyter notebooks for the code samples of the book "Deep Learning with Python"

  Language:Jupyter Notebook18.9k8.7k

• llinjupt/mlhowto

  Data Science and Machine Learning

  Language:Python304

• TheAlgorithms/Python

  All Algorithms implemented in Python

  Language:Python196k46.1k

• WepLeo/cnn_without_frame

  仅使用 numpy和 cv2，实现简单的卷积神经网络，速度较慢

  Language:Jupyter Notebook5

• jackyko1991/vnet-tensorflow

  Implementation of vnet in tensorflow for medical image segmentation

  Language:Python14167

• Fabsqrt/BitTiger

  来自硅谷的终身学习大学

  2.1k561

• loli/medpy

  Medical image processing in Python

  Language:Jupyter Notebook582139

• xiaohu2015/DeepLearning_tutorials

  The deeplearning algorithms implemented by tensorflow

  Language:Jupyter Notebook1.8k771

• xmengli/H-DenseUNet

  TMI 2018. H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes

  Language:Python534160

• agis85/anatomy_modality_decomposition

  SDNet Keras implementation

  Language:Python445

• kurolz/Books

  运维之道

  Language:Python619361

• xiaoketongxue/AI-News

  Summarize the paper and code in AI(Semantic Segmentation, Medical Segmentation,REID,Super-Resolution,Registration,CVPR,ECCV,ICCV,AAAI,MICCAI)

  37576

• huangmozhilv/u2net_torch

  MICCAI2019:3D U$^2$-Net: A 3D Universal U-Net for Multi-Domain Medical Image Segmentation

  Language:Python23553

• Tencent/MedicalNet

  Many studies have shown that the performance on deep learning is significantly affected by volume of training data. The MedicalNet project provides a series of 3D-ResNet pre-trained models and relative code.

  Language:Python2k419

• leoxiaobin/deep-high-resolution-net.pytorch

  The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

  Language:Cuda4.4k919