STMicroelectronics/st-mems-machine-learning-core
Examples, tutorials, and tools for the MLC, a dedicated core for machine learning processing embedded in STMicroelectronics MEMS sensors.
This helps embedded systems developers or electronics engineers integrate machine learning algorithms directly into STMicroelectronics MEMS sensors with a dedicated Machine Learning Core (MLC). It takes raw sensor data and configurable decision tree logic, then outputs processed results or interrupt signals from the sensor itself. This is for those designing low-power, intelligent sensing applications.
Use this if you need to perform simple machine learning tasks like activity recognition or anomaly detection directly on a MEMS sensor, reducing overall system power consumption.
Not ideal if you require complex machine learning models (e.g., deep learning) that need significant computational power beyond basic decision trees.
Stars
19
Forks
2
Language
MATLAB
License
BSD-3-Clause
Category
Last pushed
Nov 04, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/STMicroelectronics/st-mems-machine-learning-core"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
emlearn/emlearn
Machine Learning inference engine for Microcontrollers and Embedded devices
analogdevicesinc/ai8x-training
Model Training for ADI's MAX78000 and MAX78002 Edge AI Devices
DT42/BerryNet
Deep learning gateway on Raspberry Pi and other edge devices
SummerGift/EmbeddedSystem
:books: 计算机体系架构、嵌入式系统基础与主流编程语言相关内容总结
eclypse-org/eclypse
An Edge-Cloud python platform for simulated (and emulated) runtime environments