zhyhan

AD3DMIL

Attention Based Deep 3D Multiple Instance Learning

Spine-GAN

A generative adversarial network for spinal image segmentation and radiological grading.

RDA

Robust Domain Adaptation under Noisy Environments

TransPar

Learning Transferable Parameters for Unsupervised Domain Adaptation

DATE

Public code of AAAI 2023 paper "Discriminability and Transferability Estimation: A Bayesian Source Importance Estimation Approach for Multi-Source-Free Domain Adaptation"

spine-reports-gene

A framework for generating radiological reports of spine MRIs using logic reasoning and visual perception.

covid-19-detection

The implementation of "Deep Learning-based Detection for COVID-19 from Chest CT using Weak Label".

lungmask

Automated lung segmentation in CT

pathology

pathology-multiresolution

Multiresolution pathological image study

Transfer-Learning-Library

Transfer Learning Library for Domain Adaptation and Finetune.

zhyhan.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

awesome-domain-adaptation

A collection of AWESOME things about domian adaptation

AlignCLIP

AlignCLIP: Navigating the Misalignments for Robust Vision-Language Generalization

APLCLIP

Anticausal Prompt Learning for CLIP

awesome-prolog

⚡️ Curated list of Prolog packages and resources

BNUGraduateThesis

My graduation thesis

camelyon17

Camelyon17-1

DMML-Net

KD3A

Here is the official implementation of the model KD3A in paper "KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation".

L_DMI

Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"

NCRF

Cancer metastasis detection with neural conditional random field (NCRF)

NRC_SFDA

Code for our NeurIPS 2021 paper 'Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation'

Pathology-Backup

pt-dec

PyTorch implementation of DEC (Deep Embedding Clustering)

python-mode

Vim python-mode. PyLint, Rope, Pydoc, breakpoints from box.

SHOT

code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"

weread2notion-pro