Human-Activity-Recognition-using-CNN and har-keras-cnn
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.
About har-keras-cnn
ni79ls/har-keras-cnn
Jupyter Notebook for Human Activity Recognition (HAR) with 1D Convolutional Neural Network in Python and Keras
This helps sports scientists, fitness researchers, or anyone analyzing human movement automatically identify different activities from sensor data. You input raw accelerometer data, typically from wearable devices, and it outputs predictions classifying movements like walking, running, or jogging. It's designed for practitioners who need to categorize physical activities based on time-series sensor readings.
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