ROC5COR/STM32_NeuralNet_MovementDetection
Motion recognition with artificial intelligence on STM32
This project helps embedded systems engineers and researchers experiment with deploying and training small neural networks for motion recognition directly on an STM32 microcontroller. You would input accelerometer data, and the system outputs recognized motion patterns. This is ideal for those working on battery-powered devices or applications where real-time, on-device AI inference and training are critical.
No commits in the last 6 months.
Use this if you are an embedded systems engineer or researcher who needs to implement and train motion detection using neural networks directly on an STM32 microcontroller with accelerometer data.
Not ideal if you are looking for a pre-trained, high-accuracy motion recognition solution for general-purpose computing or cloud-based applications.
Stars
19
Forks
8
Language
C
License
—
Category
Last pushed
Feb 06, 2018
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/ROC5COR/STM32_NeuralNet_MovementDetection"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
roboflow/inference
Turn any computer or edge device into a command center for your computer vision projects.
roboflow/roboflow-python
The official Roboflow Python package. Manage your datasets, models, and deployments. Roboflow...
dusty-nv/jetson-inference
Hello AI World guide to deploying deep-learning inference networks and deep vision primitives...
hailo-ai/tappas
High-performance, optimized pre-trained template AI application pipelines for systems using Hailo devices
Apra-Labs/ApraPipes
A pipeline framework for developing video and image processing application. Supports multiple...