Jianhong Cheng (chengjianhong)

chengjianhong

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Company:Central South University

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Jianhong Cheng's repositories

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3D-CycleGan-Pytorch-MedImaging

Pytorch pipeline for 3D image domain translation using Cycle-Generative-Adversarial-networks, without paired examples.

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AMR-Benchmark

A Unified Implementation of Several Baseline Deep Learning Models for Automatic Modulation Recognition

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ares

A Python library for adversarial machine learning focusing on benchmarking adversarial robustness.

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Awesome-Federated-Learning

Federated Learning Library: https://fedml.ai

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brain_mask

3D deep convolutional neural network based segmentation and brain masking tool for multi-modal brain MRI

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CoTr

[MICCAI2021] CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation

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CSUthesis

中南大学研究生学位论文LaTex模版(博士和硕士)

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D2Net

D2Net for brain tumor segmentation with missing modalities

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dino

PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

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fedavg.pytorch

A PyTorch implementation of "Communication-Efficient Learning of Deep Networks from Decentralized Data", AISTATS, 2017

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FedBN

[ICLR'21] FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

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lifelines

Survival analysis in Python

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models

Models and examples built with TensorFlow

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Patch-GCN

Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks - MICCAI 2021

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pycox

Survival analysis with PyTorch

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research-contributions

Implementations of recent research prototypes/demonstrations using MONAI.

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segtran

Medical Image Segmentation using Squeeze-and-Expansion Transformers

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simclr

SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

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WSISA

Zhu, Xinliang, et al. "Wsisa: Making survival prediction from whole slide histopathological images." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2017.

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WSISIA_

implement "WSISA: Making Survival Prediction from Whole Slide Histopathological Images"

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