Human-Activity-Recognition-using-CNN and Deep-Learning-for-Human-Activity-Recognition

Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 9/25
Maturity 16/25
Community 19/25
Stars: 486
Forks: 219
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Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 74
Forks: 17
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About Human-Activity-Recognition-using-CNN

aqibsaeed/Human-Activity-Recognition-using-CNN

Convolutional Neural Network for Human Activity Recognition in Tensorflow

This project helps you classify everyday physical actions, like walking, jogging, or sitting, from sensor data. It takes raw data from smartphone accelerometers and gyroscopes and tells you exactly what activity a person was performing. This tool is useful for researchers or product developers working with wearable technology or health monitoring applications.

wearable-tech activity-tracking motion-sensing health-monitoring behavior-analysis

About Deep-Learning-for-Human-Activity-Recognition

takumiw/Deep-Learning-for-Human-Activity-Recognition

Keras implementation of CNN, DeepConvLSTM, and SDAE and LightGBM for sensor-based Human Activity Recognition (HAR).

This project helps classify human activities like walking, standing, or sitting using data from smartphone sensors. It takes raw accelerometer and gyroscope readings and outputs a prediction of the activity being performed. This is useful for researchers or developers creating applications that need to understand user movement and behavior.

activity-recognition wearable-tech sensor-data-analysis behavioral-analytics mobile-health

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