Pinned Repositories
active-learning-pretrained-models
Active Learning Helps Pretrained Models Learn the Intended Task (https://arxiv.org/abs/2204.08491) by Alex Tamkin, Dat Nguyen, Salil Deshpande, Jesse Mu, and Noah Goodman
awesome-active-learning
A curated list of awesome Active Learning
Awesome-Diabetic-Retinopathy-Detection
Papers and Public Datasets for Diabetic Retinopathy Detection
awesome-self-supervised-learning
A curated list of awesome self-supervised methods
CNN-VAE
Variational Autoencoder (VAE) with perception loss implementation in pytorch
Code
fdujay.github.io
BY Blog ->
MedSL
Medical application using Self-supervised Learning
OpenSelfSup
Self-Supervised Learning Toolbox and Benchmark
pytorch-handbook
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
fdujay's Repositories
fdujay/awesome-self-supervised-learning
A curated list of awesome self-supervised methods
fdujay/OpenSelfSup
Self-Supervised Learning Toolbox and Benchmark
fdujay/active-learning-pretrained-models
Active Learning Helps Pretrained Models Learn the Intended Task (https://arxiv.org/abs/2204.08491) by Alex Tamkin, Dat Nguyen, Salil Deshpande, Jesse Mu, and Noah Goodman
fdujay/awesome-active-learning
A curated list of awesome Active Learning
fdujay/Awesome-Diabetic-Retinopathy-Detection
Papers and Public Datasets for Diabetic Retinopathy Detection
fdujay/CNN-VAE
Variational Autoencoder (VAE) with perception loss implementation in pytorch
fdujay/Code
fdujay/fair_self_supervision_benchmark
Scaling and Benchmarking Self-Supervised Visual Representation Learning
fdujay/FastFCN
FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation.
fdujay/fdujay.github.io
BY Blog ->
fdujay/GLNet
[CVPR 2019, Oral] "Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-High Resolution Images" by Wuyang Chen*, Ziyu Jiang*, Zhangyang Wang, Kexin Cui, and Xiaoning Qian
fdujay/MedSL
Medical application using Self-supervised Learning
fdujay/pytorch-handbook
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
fdujay/KaryoNet
fdujay/Learning-Loss-for-Active-Learning
Reproducing experimental results of LL4AL [Yoo et al. 2019 CVPR]
fdujay/MAE-pytorch
Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners
fdujay/modAL
A modular active learning framework for Python
fdujay/NPID
A PyTorch implementation of NPID based on CVPR 2018 paper "Unsupervised Feature Learning via Non-Parametric Instance Discrimination"
fdujay/One-shot-AL
fdujay/online_img
fdujay/pycuda_drr
Digitally recconstructed radiograph
fdujay/pytorch-DR
Implementation of team o_O solution for the Kaggle Diabetic Retinopathy Detection Challenge in pytorch.
fdujay/pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
fdujay/Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
fdujay/pytorch_classification
利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码
fdujay/self-supervised-3d-tasks
fdujay/SIIM-ISIC-challenge
Project of SIIM-ISIC challenge
fdujay/skin-data-augmentation
Source code for the paper 'Data Augmentation for Skin Lesion Analysis' - Best Paper Award at the ISIC Skin Image Analysis Workshop @ MICCAI 2018
fdujay/swav
PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882
fdujay/ultralytics
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite