https://github.com/billy-enrizky/activity-recognition-project
"Embark on a cutting-edge journey in Human Activity Recognition using a fusion of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. This project includes model training, metric visualization, and action prediction in videos. Experience seamless interaction with a Streamlit-powered user-friendly version (at the bottom)
https://github.com/billy-enrizky/activity-recognition-project
activity-recognition convolutional-neural-networks deep-learning human-activity-recognition humanactivityrecognition lstm-neural-networks machine-learning neural-network streamlit
Last synced: 8 months ago
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"Embark on a cutting-edge journey in Human Activity Recognition using a fusion of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. This project includes model training, metric visualization, and action prediction in videos. Experience seamless interaction with a Streamlit-powered user-friendly version (at the bottom)
- Host: GitHub
- URL: https://github.com/billy-enrizky/activity-recognition-project
- Owner: billy-enrizky
- License: mit
- Created: 2023-12-30T22:05:16.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-03-12T22:17:18.000Z (over 1 year ago)
- Last Synced: 2024-03-12T23:31:35.717Z (over 1 year ago)
- Topics: activity-recognition, convolutional-neural-networks, deep-learning, human-activity-recognition, humanactivityrecognition, lstm-neural-networks, machine-learning, neural-network, streamlit
- Language: Jupyter Notebook
- Homepage: https://billy-enrizky.github.io/Activity-Recognition-Project/
- Size: 94.8 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE