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

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

[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

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

vendor independent TinyML deep learning library, compiler and inference framework microcomputers and micro-controllers

Instructions, source code, and misc. resources needed for building a Tiny ML-powered artificial nose.

Machine Learning inference engine for Microcontrollers and Embedded devices

[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning

Code for MobiCom paper 'TinyML-CAM: 80 FPS Image Recognition in 1 Kb RAM'

Seeed SenseCraft Model Assistant is an open-source project focused on embedded AI.

A research library for pytorch-based neural network pruning, compression, and more.

Notes on Machine Learning on edge for embedded/sensor/IoT uses

Rune provides containers to encapsulate and deploy edgeML pipelines and applications

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

In this repository you will find TinyML course syllabi, assignments/labs, code walkthroughs, links to student projects, and lecture videos (where applicable).

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 holds the Google Colabs for the EdX TinyML Specialization

Spying on Microcontrollers using Current Sensing and embedded TinyML models

在ESP32上实现基于红外热成像阵列传感器的手势识别

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