Popular GitHub Repositories for Microcontroller

TinyML AI inference library

A higher-level Neural Network library for microcontrollers.

[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256KB Memory

Machine Learning inference engine for Microcontrollers and Embedded devices

Open Neural Network Exchange to C compiler.

Intelligent Robotic Arm is a 5 dof autonomous arm with webcam attached to it for vision.

A tool to support using classification models in low-power and microcontroller-based embedded systems.

Supplementary material for IEEE Services Computing paper 'An SRAM Optimized Approach for Constant Memory Consumption and Ultra-fast Execution of ML Classifiers on TinyML Hardware'

Compress, Deploy and Inference YOLOv7 on low-cost MCUs

Edge Computing using Tensorflow Lite

Building a security camera with ESP32-CAM and workers-ai for object detection

Code, Documentation, and Demo, of an autonomous car that tracks a black line as well as markers in the form of sign posts.

My Thesis: Auto-ML Tool for IoT Applications Version 1.0

TFLite applications: Optimized .tflite models (i.e. lightweight and low latency) and code to run directly on your Microcontroller!

Tensorflow lite used on a SAMD21 microcontroller in the arduino framework for activity recognition

This GitHub repository provides a detailed guide for deploying TensorFlow Lite (TFLite) models on the Sony Spresense board.

? CNN model for birdsong classification on an embedded microcontroller which then sends the predictions wirelessly via LoRaWAN to TTN. Made as part of a school project.

Wake word detection using Tiny ML. Tensorflow lite is used here. The project has been done by refering the text book, Tiny ML by O' Reilly.

About An AI model has been implemented to detect potato, onion & tomato on a resource constrained hardware

Code and resources for the paper: Real-Time Student Engagement Monitoring on Edge Devices: Deep Learning Meets Efficiency and Privacy