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Joy's Projects

blockchain-real-estate icon blockchain-real-estate

🚀基于区块链的房地产交易系统小模型。提供销售和捐赠功能。本项目使用Hyperledger Fabric构建区块链网络, go编写智能合约,应用层使用gin+fabric-sdk-go调用合约。前端展示使用vue+element。体验地址:http://blockchain.togettoyou.com/web

cesium icon cesium

An open-source JavaScript library for world-class 3D globes and maps :earth_americas:

data-privacy icon data-privacy

Preserve data privacy with k-anonymity (samarati & mondrian), differential privacy, federated learning, paillier homomorphic encryption, etc.

examination_system- icon examination_system-

这是个基于SSM+Bootstrap的教务查询系统,是一个简单的教务查询系统,增删改查练手小项目,熟悉SSM的整合开发,使用技术 IOC容器:Spring Web框架:SpringMVC ORM框架:Mybatis 数据源:C3P0 日志:log4j 前端框架:Bootstrap 运行环境 jdk8+tomcat8+mysql+Eclipse+maven 项目技术(必填) spring+spring mvc+mybatis+bootstrap+jquery前人栽树后人乘凉,这个是github某个作者写的,原系统是IDEA开发,本人修改为了eclipse版本。欢迎下载。

fabric icon fabric

Hyperledger Fabric is an enterprise-grade permissioned distributed ledger framework for developing solutions and applications. Its modular and versatile design satisfies a broad range of industry use cases. It offers a unique approach to consensus that enables performance at scale while preserving privacy.

fed icon fed

A try for federated learning with Resnet on CIFAR10 using Cloud-Edge-Client framework.

fed-att icon fed-att

Attentive Federated Learning for Private NLM

federated icon federated

A framework for implementing federated learning

federated-learning icon federated-learning

An open source FL implement with dataset(Femnist, Shakespeare, MNIST, Cifar-10 and Fashion-Mnist) using pytorch

forestblog icon forestblog

一个简单漂亮的SSM(Spring+SpringMVC+Mybatis)博客系统

lanlaninterview icon lanlaninterview

此仓库将包含各大银行的基本介绍,笔试面试特点,发现这个宝库就离上岸不远了,哼

niid-bench icon niid-bench

Federated Learning on Non-IID Data Silos: An Experimental Study

o-cnn icon o-cnn

O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis

secureaggregation icon secureaggregation

An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawitz et. al)" in Python.

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