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.
165 stars. No commits in the last 6 months.
Use this if you need to classify human physical activities from wearable sensor data with high accuracy and are comfortable working with Python and machine learning models.
Not ideal if you need to analyze static, non-sequential data or if you prefer a tool with a graphical user interface.
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75
Language
Python
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Last pushed
Mar 19, 2023
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