yuanjinghui Goto Github PK

atspm

ATSPM Data Visulization

atspm-data-process

ATSPM-Data-Process

attentionconvlstm

"Attention in Convolutional LSTM for Gesture Recognition" in NIPS 2018

copy-files-across-folders

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++

deepst

Deep Learning for Spatio-Temporal Data

dmvst-net

DMVST-Net for AAAI 2018

human-activity-recognition-with-neural-network-using-gyroscopic-and-accelerometer-variables

The VALIDATION ACCURACY is BEST on KAGGLE. Artificial Neural Network with a validation accuracy of 97.98 % and a precision of 95% was achieved from the data to learn (as a cellphone attached on the waist) to recognise the type of activity that the user is doing. The dataset's description goes like this: The sensor signals (accelerometer and gyroscope) were pre-processed by applying noise filters and then sampled in fixed-width sliding windows of 2.56 sec and 50% overlap (128 readings/window). The sensor acceleration signal, which has gravitational and body motion components, was separated using a Butterworth low-pass filter into body acceleration and gravity. The gravitational force is assumed to have only low frequency components, therefore a filter with 0.3 Hz cutoff frequency was used.

opencv

Open Source Computer Vision Library

smart-city-k-means-decision-tree-gb

smart-city-knn

smart-city-svr-ann

statistical-computing-hw1

Homework1

statistical-computing-project-2

Project 2

statistical-computing-project1

Project and assignment for Statistical Computing

stdn

Code for our Spatiotemporal Dynamic Network

stgcn_ijcai-18

Spatio-Temporal Graph Convolutional Networks

vdotsmartroaddatadownloader

yuanjinghui.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

yuanjinghui1.github.io

:sparkles: Build a beautiful and simple website in literally minutes. Demo at http://deanattali.com/beautiful-jekyll