ReilYoung
Architectural Human Factors Science in the Context of Artificial Intelligence
Tsinghua UniversityBeijing, China
ReilYoung's Stars
rougier/scientific-visualization-book
An open access book on scientific visualization using python and matplotlib
olgabot/prettyplotlib
Painlessly create beautiful matplotlib plots.
rasbt/matplotlib-gallery
Examples of matplotlib codes and plots
garrettj403/SciencePlots
Matplotlib styles for scientific plotting
jbmouret/matplotlib_for_papers
Handout for the tutorial "Creating publication-quality figures with matplotlib"
ZWharton15/Human-Pose-Classification
A Python and Keras implementation for classifying human arm poses
hafizas101/Real-time-human-pose-estimation-and-classification
haofanwang/accurate-head-pose
Pytorch code for Hybrid Coarse-fine Classification for Head Pose Estimation
cbsudux/awesome-human-pose-estimation
A collection of awesome resources in Human Pose estimation.
bdy9527/SDCN
Structural Deep Clustering Network
thuservices/thuservices
https://thu.services
vbhavank/IASSA-Saliency
Source code for our WACV 2020 paper ``Iterative and Adaptive Sampling with Spatial Attention for Black-Box Model Explanations" https://arxiv.org/abs/1912.08387
Tiger101010/DAEGC
PyTorch implementation of Deep Attention Embedding Graph Clustering (19IJCAI) https://www.ijcai.org/Proceedings/2019/0509.pdf
d-ailin/GDN
Implementation code for the paper "Graph Neural Network-Based Anomaly Detection in Multivariate Time Series" (AAAI 2021)
snigdha89/Pose-Estimation-and-Clustering-of-60-Exercises
There is a dataset of human poses while exercising in the gym. The activities are named as the first column. The pose-output.csv file is the result of feeding many exercise videos file into a pose estimation algorithm (i.e., Blazepose https://ai.googleblog.com/2020/08/on-device-real-time-body-posetracking. html). Each exercise is a tensor (three-dimension data, i.e., x,y,z and time) (1) Create a visualization that as an input we feed an exercise and creates a visualization of the physical activity as an animation or gif. (2) For each exercise, identify joints that are moving, and list them. Besides, identify joints that are not moving as well. (3) List the degree of changes between joints. For example, take a look at following the output of your algorithm should be as follows: {Moving: right_wrist, right_shoulder, Angle_changes: right_elbow {degree: 175, 170, … 30, 35, … 180} } {Not_Moving: right_hip, right_knee, right_heel, left_shoulder, left_elbow, …} (4)
trinh064/ClusteringMonkeyPoses
Use SimpleBaseline model to detect poses of primates, then cluster similar poses together to find most common poses
dnjstlr555/iPose
Human pose embedding and clustering using OpenPose and AutoEncoder
amirmk89/gepc
Graph Embedded Pose Clustering for Anomaly Detection
ML4ITS/mtad-gat-pytorch
PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).
Niloy-Chakraborty/Time-Series_Clustering_For_Smart_Meter_Dataset
EDA and Time Series Stream Clustering for London Smart Meter Dataset, using Autoencoder with Kmeans algorithm, DB Scan, and Hierarchical Clustering algorithm.
TimyadNyda/Variational-Lstm-Autoencoder
Lstm variational auto-encoder for time series anomaly detection and features extraction
mmakos/HPC
Human Pose Classification
dronefreak/human-action-classification
This repository allows you to classify 40 different human actions. Pose detection, estimation and classification is also performed. Poses are classified into sitting, upright and lying down.
rodrigobressan/entity_embeddings_categorical
Discover relevant information about categorical data with entity embeddings using Neural Networks (powered by Keras)
greenbellpepper/GreenPepper
MAIF/shapash
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
lin-shuyu/VAE-LSTM-for-anomaly-detection
We propose a VAE-LSTM model as an unsupervised learning approach for anomaly detection in time series.
aqibsaeed/Entity-Embedding-with-LSTM-for-Time-Series
Entity Embedding with LSTM for Time Series
AnubhavGupta3377/Text-Classification-Models-Pytorch
Implementation of State-of-the-art Text Classification Models in Pytorch
gdetor/pytorch_time2vec