tinyml

[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment

Header-only library for using Keras models in C++.

This is a list of interesting papers and projects about TinyML.

Machine Learning inference engine for Microcontrollers and Embedded devices

TensorFlow Lite models for MIRNet for low-light image enhancement.

Spying on Microcontrollers using Current Sensing and embedded TinyML models

This is the TinyML programs for ESP32 according to BlackWalnut Labs Tutorials. (黑胡桃实验室的TinyML教程中的程序集合)

This repository shows how to train a custom detection model with the TFOD API, optimize it with TFLite, and perform inference with the optimized model.

Launched in March 2020 in response to the coronavirus disease 2019 (COVID-19) pandemic, COVID-Net is a global open source, open access initiative dedicated to accelerating advancement in machine learning to aid front-line healthcare workers and clinical institutions around the world fighting the continuing pandemic. Towards this goal, our global multi-disciplinary team of researchers, developers, and clinicians have made publicly available a suite of tailored deep neural network models for tackling different challenges ranging from screening to risk stratification to treatment planning for patients with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Furthermore, we have made available fully curated, open access benchmark datasets comprised of some of the largest, most diverse patient cohorts from around the world.

Conserve water with image classification for plant droop detection deployed on the Arduino platform.

CMix-NN: Mixed Low-Precision CNN Library for Memory-Constrained Edge Devices

Code for IoT Journal paper title 'ML-MCU: A Framework to Train ML Classifiers on MCU-based IoT Edge Devices'

A tinyML system using a Raspberry Pi Pico and TensorFlow Lite for Microcontrollers to detect loud talking. It can be utilized to encourage people to eat quietly to prevent the spread of the coronavirus and help in the fight against COVID

Code for paper: 'Multi-Component Optimization and Efficient Deployment of Neural-Networks on Resource-Constrained IoT Hardware' (paper under review)

The EEMBC EnergyRunner application framework for the MLPerf Tiny benchmark.

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

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

MicroSpeech Wake Word example on the Raspberry Pi Pico. This is a port of the example on the TensorFlow repository.

Magic Wand using ESPectro32 or other ESP32 boards, powered by TensorFlow Lite for Microcontrollers and PlatformIO

The TinyML "Hello World" sine wave model on Arduino Uno v3

Collection of media arts instruments using tiny machine learning, and based on microcontrollers.

Repo of the demo paper: TinyML Benchmark: Executing Fully Connected Neural Networks on Commodity Microcontrollers

TinyML for STM32F407 using different frameworks in C and C++ with Keil uVision IDE.

TensorFlow Lite C/C++ library for microcontrollers.

Recognize spoken words on device using an Adafruit EdgeBadge and a TinyML model