Pinned Repositories
TTADC
[MICCAI'22] Test-time Adaptation with Calibration of Medical Image Classification Nets for Label Distribution Shift
awesome-causality-algorithms
An index of algorithms for learning causality with data
Awesome-Learning-with-Label-Noise
A curated list of resources for Learning with Noisy Labels
COVID-MTL
Multitask learning for automated COVID 19 diagnosis and severity assessment using CT scans
Deep-Diabetic-Retinopathy-Image-Dataset-DeepDRiD-
Automated machine learning can facilitate the early diagnosis and timely treatment of diabetic retinopathy. Following the 1st Diabetic Retinopathy: Segmentation and Grading Challenge held with ISBI in 2018, we would like to promote the progress further through 2nd challenge using a new dataset, Deep Diabetic Retinopathy Image Dataset (DeepDRiD). The challenge is subdivided into three tasks as follows: A. Dual-View Disease Grading: Classification of fundus images according to the severity level of diabetic retinopathy using dual view retinal fundus images. B. Image Quality Estimation: Fundus quality assessment for overall image quality, artifacts, clarity, and field definition. C. Transfer Learning: Explore the generalizability of a Diabetic Retinopathy (DR) grading system. The robust and generalizable models are expected to be developed to solve clinical issues in reality.
dl_for_GCTB
Endo-FM
[MICCAI'23] Foundation Model for Endoscopy Video Analysis via Large-scale Self-supervised Pre-train
FedBN
[ICLR'21] FedBN: Federated Learning on Non-IID Features via Local Batch Normalization
mgcpy-old
MGCPY WILL NO LONGER BE UPDATED. THE NEW REPO CAN BE FOUND HERE:
pytorch-meta
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
WenaoMA's Repositories
WenaoMA/pytorch-meta
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
WenaoMA/awesome-causality-algorithms
An index of algorithms for learning causality with data
WenaoMA/Awesome-Learning-with-Label-Noise
A curated list of resources for Learning with Noisy Labels
WenaoMA/COVID-MTL
Multitask learning for automated COVID 19 diagnosis and severity assessment using CT scans
WenaoMA/Deep-Diabetic-Retinopathy-Image-Dataset-DeepDRiD-
Automated machine learning can facilitate the early diagnosis and timely treatment of diabetic retinopathy. Following the 1st Diabetic Retinopathy: Segmentation and Grading Challenge held with ISBI in 2018, we would like to promote the progress further through 2nd challenge using a new dataset, Deep Diabetic Retinopathy Image Dataset (DeepDRiD). The challenge is subdivided into three tasks as follows: A. Dual-View Disease Grading: Classification of fundus images according to the severity level of diabetic retinopathy using dual view retinal fundus images. B. Image Quality Estimation: Fundus quality assessment for overall image quality, artifacts, clarity, and field definition. C. Transfer Learning: Explore the generalizability of a Diabetic Retinopathy (DR) grading system. The robust and generalizable models are expected to be developed to solve clinical issues in reality.
WenaoMA/dl_for_GCTB
WenaoMA/Endo-FM
[MICCAI'23] Foundation Model for Endoscopy Video Analysis via Large-scale Self-supervised Pre-train
WenaoMA/FedBN
[ICLR'21] FedBN: Federated Learning on Non-IID Features via Local Batch Normalization
WenaoMA/mgcpy-old
MGCPY WILL NO LONGER BE UPDATED. THE NEW REPO CAN BE FOUND HERE:
WenaoMA/Swin-Transformer
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
WenaoMA/TransUNet
This repository includes the official project of TransUNet, presented in our paper: TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.
WenaoMA/TTADC