tcchriszhao's repositories
-radar-prmt-android
Application to be run on an Android device to interact with the wearable devices & phone sensors for passive data streaming
AcquisitionEEG2020
EEG Acquisition board software, PCB design files and documentation.
androidSensorServer
Android app which stream phone's motion sensors to websocket clients ( PC , raspberry pi , arduino , webbrowser etc ) over Wi-Fi and USB
Awesome-Learning-with-Label-Noise
A curated list of resources for Learning with Noisy Labels
awesome-open-gpt
Collection of Open Source Projects Related to GPT，GPT相关开源项目合集🚀、精选🔥🔥
DepressionEstimation
Bachelor Thesis - Deep Learning-based Multi-modal Depression Estimation
EEG-Datasets
A list of all public EEG-datasets
EEG-emotions
Application prepares data to learning process. Including preprocessing, cleaning, reformating, feature extraction using PyEEG library and learning using Sklearn tool.
EEG-Feature-Extraction-Toolbox
This toolbox offers 30 types of EEG feature extraction methods (HA, HM, HC, and etc.) for Electroencephalogram (EEG) applications.
EI328-project
Project for course EI328. Unsupervised Domain Adaptation on EEG-based Sentiment Classification
feature-selector
Feature selector is a tool for dimensionality reduction of machine learning datasets
featuretools
An open source python library for automated feature engineering
lantern
Lantern官方版本下载 蓝灯 翻墙 代理 科学上网 外网 加速器 梯子 路由 lantern proxy vpn censorship-circumvention censorship gfw accelerator
mobile-aloha
Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation
motor_activity_DepressionDetection
My final year dissertation project. This project takes motor activity data from a control group and a condition group. The data is filtered, cleaned and transformed for appropriate use to find the "best" classification algorithm to identify depressed patients from non-depressed patients
Multimodal-Emotion-Recognition
A real time Multimodal Emotion Recognition web app for text, sound and video inputs
OpenSelfSup
Self-Supervised Learning Toolbox and Benchmark
Predicting-Depression
Project using machine learning to predict depression using health care data from the CDC NHANES website. A companion dashboard for users to explore the data in this project was created using Streamlit. Written with python using jupyter notebook for the main project flow/analysis and visual studio code for writing custom functions and creating the dashboard.
radar-android-phone
Basic phone sensor plugin for RADAR passive remote monitoring app