Zhengyushan
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MICCAI'24 - DiRecT: Diagnosis and Reconstruction Transformer for Mandibular Deformity Assessment
Repository for paper "HyperGraph Learning Network for Weakly Supervised Histopathology Whole Slide Image Classification."
A python (PyTorch) implementation of Polar Transform Network (PTN) method for prostate ultrasound segmentation
A python (PyTorch) implementation of Shadow-consistent Semi-supervised Learning (SCO-SSL) method for prostate ultrasound segmentation
Caffe with 3D CRF-RNN for medical image analysis
A C++ (Caffe) implementation of Triple-branch FCN for multi-organ localization in CT images
Asymmetric Multi-Task Attention Network for Prostate Bed Segmentation in CT Images
A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.
Graphormer is a general-purpose deep learning backbone for molecular modeling.
Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering
A list of Contrastive Learning Papers&Codes. Unsupervised: MoCo/SimCLR/SwAV/BYOL/SimSiam
PyTorch implementation of Contrastive Learning methods
PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722
label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful
Please choose the openseg.pytorch project for the updated code that achieve SOTA on 6 benchmarks!
Pytorch implementation of BMVC 2019 paper Dual Graph Convolutional Network for Semantic Segmentation.
Code for the KDD 2018 paper: STAMP: Short-Term Attention/Memory Priority Model for Session-based Recommendation
Program for the analysis and visualization of whole-slide images in digital pathology
A memory-efficient implementation of DenseNets
The implementation of focal loss proposed on "Focal Loss for Dense Object Detection" by KM He and support for multi-label dataset.
A convolutional neural network for graph classification in PyTorch
Must-read papers on graph neural networks (GNN)