fengweie

1st-in-MICCAI-GAMMA-2021-challenge

Algorithm_Interview_Notes-Chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

AlgorithmsByPython

算法/数据结构/Python/剑指offer/机器学习/leetcode

AttentionDeepMIL

Implementation of Attention-based Deep Multiple Instance Learning in PyTorch

fengweie.github.io

Human-Emotion-Analysis-using-EEG-from-DEAP-dataset

Processed the DEAP dataset on basis of 1) PSD (power spectral density) and 2)DWT(discrete wavelet transform) features . Classifies the EEG ratings based on Arousl and Valence(high /Low)

MICCAI2019-OpenSourcePapers

MICCAI 2019 Open Source Papers

SE_ASA

AAAI 2023 paper "Unsupervised Domain Adaptation for Medical Image Segmentation by Selective Entropy Constraint and Adaptive Semantic Alignment"

transformer_ep

Code for paper:"Development and validation of a deep learning model for treatment response prediction in newly diagnosed epilepsy."

UDA_CLR

Code for our miccai 2022 paper “Unsupervised Domain Adaptive Fundus Image Segmentation with Category-Level Regularization”.

fengweie/SE_ASA

AAAI 2023 paper "Unsupervised Domain Adaptation for Medical Image Segmentation by Selective Entropy Constraint and Adaptive Semantic Alignment"

fengweie/UDA_CLR

Code for our miccai 2022 paper “Unsupervised Domain Adaptive Fundus Image Segmentation with Category-Level Regularization”.

fengweie/fengweie.github.io

fengweie/transformer_ep

Code for paper:"Development and validation of a deep learning model for treatment response prediction in newly diagnosed epilepsy."

fengweie/1st-in-MICCAI-GAMMA-2021-challenge

fengweie/awesome-computer-vision

A curated list of awesome computer vision resources

fengweie/awesome-knowledge-distillation

Incredible transferring knowledge techniques with Knowledge distillation

fengweie/Awesome-Knowledge-Distillation-1

Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2020)。

fengweie/Awesome-Learning-with-Label-Noise

A curated list of resources for Learning with Noisy Labels

fengweie/BAPA-Net

Code for BAPA-Net: Boundary Adaptation and Prototype Alignment for Cross-domain Semantic Segmentation

fengweie/bert

fengweie/chd_cognitive

This is a pytorch implementation of the chd_cognitive project.

fengweie/dauda

fengweie/DL_CNV

fengweie/DSI-Net

DSI-Net: Deep Synergistic Interaction Network for Joint Classification and Segmentation with Endoscope Images, under review at IEEE TMI

fengweie/dsmil-wsi

DSMIL: Multiple instance learning networks for tumor detection in Whole Slide Image

fengweie/Guiding-Pseudo-labels-with-Uncertainty-Estimation-for-Source-free-Unsupervised-Domain-Adaptation

Code for "Guiding-Pseudo-labels-with-Uncertainty-Estimation-for-Source-free-Unsupervised-Domain-Adaptation" (CVPR 2023)

fengweie/hangwenlong.github.io

fengweie/LG-ER-MT

MICCAI 2020 paper "Local and Global Structure-Aware Entropy Regularized Mean Teacher Model for 3D Left Atrium Segmentation."

fengweie/ml-visuals

🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

fengweie/OCTA-Net-OCTA-Vessel-Segmentation-Network

fengweie/OKD-Reading-List

Papers for Open Knowledge Discovery

fengweie/ProCA

fengweie/query2labels

Official implementation of paper "Query2Label: A Simple Transformer Way to Multi-Label Classification".

fengweie/Seg-Uncertainty

IJCAI2020 & IJCV 2020 :city_sunrise: Unsupervised Scene Adaptation with Memory Regularization in vivo

fengweie/SETR

[CVPR 2021] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

fengweie/tcga_segmentation

Whole Slide Image segmentation with weakly supervised multiple instance learning on TCGA | MICCAI2020 https://arxiv.org/abs/2004.05024

fengweie/TransNorm

Code release for "Transferable Normalization: Towards Improving Transferability of Deep Neural Networks" (NeurIPS 2019)

fengweie/voxelmorph

Unsupervised Learning for Image Registration

fengweie/WDMT-Net

This is an official implementation of 'A Multi-task Network with Weight Decay Skip Connection Training for Anomaly Detection in Retinal Fundus Images'