yuanjinghui

Jinghui Yuan's repositories

AttentionConvLSTM

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

Language:PythonMIT010

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++

Language:Java000

DeepST

Deep Learning for Spatio-Temporal Data

Language:PythonMIT010

DMVST-Net

DMVST-Net for AAAI 2018

Language:Python010

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.

Language:Jupyter NotebookApache-2.0010