YeLusin

YeLusin's Stars

• charlesfrye/qart-codes

  QR Codes that look nice

  Language:TypeScript322

• youngfish42/Awesome-FL

  Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

  Language:Python1.4k180

• posquit0/Awesome-CV

  :page_facing_up: Awesome CV is LaTeX template for your outstanding job application

  Language:TeX22.8k4.8k

• fahadshamshad/awesome-transformers-in-medical-imaging

  A collection of resources on applications of Transformers in Medical Imaging.

  1.2k181

• international-explore/awesome-privacy-chinese

  [WIP]国内隐私合规技术交流

  39463

• shibing624/python-tutorial

  Python实用教程，包括：Python基础，Python高级特性，面向对象编程，多线程，数据库，数据科学，Flask，爬虫开发教程。

  Language:Jupyter Notebook2k399

• Xtra-Computing/NIID-Bench

  Federated Learning Benchmark - Federated Learning on Non-IID Data Silos: An Experimental Study (ICDE 2022)

  Language:Python552114

• AmberLJC/FLsystem-paper

  Federated Learning Systems Paper List

  657

• stemrollerapp/stemroller

  Isolate vocals, drums, bass, and other instrumental stems from any song

  Language:Svelte2.6k100

• Light-City/CPlusPlusThings

  C++那些事

  Language:C++38.8k8.5k

• jhcknzzm/SSFL-Benchmarking-Semi-supervised-Federated-Learning

  Benchmarking Semi-supervised Federated Learning

  Language:Python5213

• CyC2018/CS-Notes

  :books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计

  175k50.8k

• Snailclimb/JavaGuide

  「Java学习+面试指南」一份涵盖大部分 Java 程序员所需要掌握的核心知识。准备 Java 面试，首选 JavaGuide！

  Language:Java146k45.5k

• lokinko/Federated-Learning

  联邦学习

  996190

• tushar-semwal/awesome-federated-computing

  :books: :eyeglasses: A collection of research papers, codes, tutorials and blogs on Federated Computing/Learning.

  46585

• innovation-cat/Awesome-Federated-Machine-Learning

  Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond

  1.7k262

• d2l-ai/d2l-zh

  《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。

  Language:Python61.3k10.9k

• alibaba/FederatedScope

  An easy-to-use federated learning platform

  Language:Python1.3k207

• adap/flower

  Flower: A Friendly Federated Learning Framework

  Language:Python4.9k839

• shelhamer/fcn.berkeleyvision.org

  Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

  Language:Python3.3k1.5k

• yassouali/pytorch-segmentation

  :art: Semantic segmentation models, datasets and losses implemented in PyTorch.

  Language:Jupyter Notebook1.6k379

• SMILELab-FL/FedLab

  A flexible Federated Learning Framework based on PyTorch, simplifying your Federated Learning research.

  Language:Jupyter Notebook719124

• Tramac/awesome-semantic-segmentation-pytorch

  Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)

  Language:Python2.8k581

• TsingZ0/PFLlib

  37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 20 datasets.

  Language:Python1.4k285

• linhandev/dataset

  医学影像数据集列表 『An Index for Medical Imaging Datasets』

  2.5k356

• MontaEllis/Pytorch-Medical-Segmentation

  This repository is an unoffical PyTorch implementation of Medical segmentation in 2D and 3D.

  Language:Python847197

• irfanICMLL/structure_knowledge_distillation

  The official code for the paper 'Structured Knowledge Distillation for Semantic Segmentation'. (CVPR 2019 ORAL) and extension to other tasks.

  Language:Python699104

• epfml/federated-learning-public-code

  Language:Python15447

• weiaicunzai/pytorch-cifar100

  Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)

  Language:Python4.2k1.2k

• TL-System/plato

  A federated learning framework to support scalable and reproducible research

  Language:Python33679