Pinned Repositories
3D-MRI-brain-tumor-segmentation-using-autoencoder-regularization
Pytorch implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. [https://arxiv.org/abs/1810.11654]
BraTS2018-tumor-segmentation
We provide DeepMedic and 3D UNet in pytorch for brain tumore segmentation. We also integrate location information with DeepMedic and 3D UNet by adding additional brain parcellation with original MR images.
dogs_vs_cats
猫狗大战
FedNova
PyTorch implementation of FedNova (NeurIPS 2020), and a class of federated learning algorithms, including FedAvg, FedProx.
glioma_grading
Glioma_IDH
hands-on-transfer-learning-with-python
Deep learning simplified by transferring prior learning using the Python deep learning ecosystem
IDH
IDH_Prediction
Use of Deep Learning to Predict IDH status from MR Imaging
image-segmentation-keras
Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.
chengjianhong's Repositories
chengjianhong/disentangling-influence
Code to audit indirect influence in black box models.
chengjianhong/3DCNN
3D convolutional neural network for video classification
chengjianhong/image-segmentation-keras
Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.
chengjianhong/learning-rate-techniques-keras
Exploring learning rates to improve model performance
chengjianhong/disentangled-representation-papers
A curated list of research papers related to learning disentangled representations
chengjianhong/Detectron
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
chengjianhong/horovod
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
chengjianhong/Segmentation_Boundry_loss
chengjianhong/Awesome-PyTorch-Chinese
【干货】史上最全的PyTorch学习资源汇总
chengjianhong/ml-stat-util
Statistical functions based on bootstrapping for computing confidence intervals and p-values comparing machine learning models and human readers
chengjianhong/medical-datasets
tracking medical datasets, with a focus on medical imaging
chengjianhong/Deep-Learning-for-Medical-Applications
Deep Learning Papers on Medical Image Analysis
chengjianhong/nlp-architect
NLP Architect by Intel AI Lab: A Python library for exploring the state-of-the-art deep learning topologies and techniques for natural language processing and natural language understanding
chengjianhong/UNet-family
Paper and implementation of UNet-related model.
chengjianhong/SJTU-Courses
上海交通大学课程资料分享
chengjianhong/Kidney_Tumor_Segmentation
Kidney_Tumor_Segmentation 2019
chengjianhong/see
Code for the AAAI 2018 publication "SEE: Towards Semi-Supervised End-to-End Scene Text Recognition"
chengjianhong/adverserial-autoencoder-keras
Keras Implementation of adverserial autoencoder (AAE)
chengjianhong/keras-vis
Neural network visualization toolkit for keras
chengjianhong/LungSegmentation
Lung Segmentation
chengjianhong/keras_mixup_generator
How to do mixup training from image files in Keras
chengjianhong/CapsLayer
CapsLayer: An advanced library for capsule theory
chengjianhong/Brain_tumor_segmentation
chengjianhong/OpenPC
An open source multi-element generalized polynomial chaos toolbox for matlab
chengjianhong/Lung-Segmentation
Segmentation of Lungs from Chest X-Rays using Fully Connected Networks
chengjianhong/hands-on-transfer-learning-with-python
Deep learning simplified by transferring prior learning using the Python deep learning ecosystem
chengjianhong/IDH
chengjianhong/BraTS2018-tumor-segmentation
We provide DeepMedic and 3D UNet in pytorch for brain tumore segmentation. We also integrate location information with DeepMedic and 3D UNet by adding additional brain parcellation with original MR images.
chengjianhong/keras-aae
Implementation of Adversarial Autoencoder in Keras
chengjianhong/dense3dCrf
Fully-connected (dense) 3D CRF for processing biomedical scans