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Niefengxxx's Projects

cs-notes icon 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、Java、Python、C++

dgl icon dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

easycv icon easycv

An all-in-one toolkit for computer vision

grnn icon grnn

Official implementation of "GRNN: Generative Regression Neural Network - A Data Leakage Attack for Federated Learning"

hangzhou_house_knowledge icon hangzhou_house_knowledge

2017年买房经历总结出来的买房购房知识分享给大家,希望对大家有所帮助。买房不易,且买且珍惜。Sharing the knowledge of buy an own house that according to the experience at hangzhou in 2017 to all the people. It's not easy to buy a own house, so I hope that it would be useful to everyone.

infosec_getting_started icon infosec_getting_started

A collection of resources/documentation/links/etc to help people learn about Infosec and break into the field.

interview icon interview

📚 C/C++ 技术面试基础知识总结,包括语言、程序库、数据结构、算法、系统、网络、链接装载库等知识及面试经验、招聘、内推等信息。This repository is a summary of the basic knowledge of recruiting job seekers and beginners in the direction of C/C++ technology, including language, program library, data structure, algorithm, system, network, link loading library, interview experience, recruitment, recommendation, etc.

lama icon lama

🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

mask_rcnn icon mask_rcnn

Mask R-CNN on Keras and TensorFlow,个人注释版

nlp_ability icon nlp_ability

总结梳理自然语言处理工程师(NLP)需要积累的各方面知识,包括面试题,各种基础知识,工程能力等等,提升核心竞争力

pytorch-loss icon pytorch-loss

label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful

rekcarc-tsc-uht icon rekcarc-tsc-uht

清华大学计算机系课程攻略 Guidance for courses in Department of Computer Science and Technology, Tsinghua University

sepnet icon sepnet

Pytorch implementation of "Depth-Wise Separable Convolutions and Multi-Level Pooling for an Efficient Spatial CNN-Based Steganalysis"

ssl-backdoor icon ssl-backdoor

Official implementation of the paper "Backdoor Attacks on Self-Supervised Learning".

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