jiayuanyuan1011 Goto Github PK
Name: JiaYuanyuan
Type: User
Company: Egret
Bio: Adversity is a good discipline. Adversity leads to prosperity.
Location: intern of web Front End Enginee
Name: JiaYuanyuan
Type: User
Company: Egret
Bio: Adversity is a good discipline. Adversity leads to prosperity.
Location: intern of web Front End Enginee
Volumetric CNN for feature extraction and object classification on 3D data.
500 Lines or Less
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
open-source electronics prototyping platform
基于python2的自动化测试框架
video-understanding:Video Classification, Action Recognition, Video Datasets
The web-based visual programming editor.
BOXZ is is an open source robot platform for DIY interactive entertainments!
Sample code for Channel 9 Python for Beginners course
Caffe models in TensorFlow
Caffe: a fast open framework for deep learning.
Build a web project demo of SpringMVC and Mybatis by using IDEA with maven.
cloud point to depth and rgb image
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
It is the first time for me to code wbesite of Egret company so that I need to memorize it the important time.
A technical report on convolution arithmetic in the context of deep learning
Robust 3D Hand Pose Estimation in Single Depth Images: from Single-View CNN to Multi-View CNNs
CYaRon: Yet Another Random Olympic-iNformatics test data generator
Classification and Segmentation of the MNIST dataset given as a point set input. Classification: the program classifies hand written digits, given as a sample of 100 points in a 2 dimensional field. the architecture is based on a Stanford article of a PointNet which is especially efficient for 3D image classification. the PointNet classification accuracy is 92.86% Segmentation: this is an extension to the classification net which can later define segments within the pointset. the program receives an input of a handwritten digit, given as a sample of 200 points in a 2 dimensional field, where 100 of the points are a sample of the digit itself, and the rest of the points are "background" points which are not part of the digit. the program classifies each point into one of the 2 segments and returns if it is part of the digit or part of the background. the PointNet segmentation accuracy is 97.65%
utilizing PointNet+ PCL for object detection, classification and pose estimation from point clouds
kubernetes 相关 images 同步
Doraemon-接口自动化测试工具
2019新型冠状病毒疫情时间序列数据仓库 | COVID-19/2019-nCoV Infection Time Series Data Warehouse
Fast R-CNN
Volumetric 3D Mapping in Real-Time on a CPU
FastSLAM with GUI
Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.
Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (http://fcn.berkeleyvision.org)
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.