🚀 A fast WebAssembly interpreter and the most universal WASM runtime

[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

Open Neural Network Exchange to C compiler.

Haiway Edge Computing OS

SLEdge: a serverless runtime designed for the Edge.

Vision Components MIPI CSI-2 driver for NVIDIA Jetson Nano, Xavier NX, AGX Xavier, TX2 and Orin Nano, Orin NX

Mobilenet v1 trained on Imagenet for STM32 using extended CMSIS-NN with INT-Q quantization support

A Portable C Library for Distributed CNN Inference on IoT Edge Clusters

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

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

microblx: real-time, embedded, reflective function blocks.

ANT (AI-based Networked Things) Framework

Huawei CodeLab - IoT

Code for paper 'Train++: An Incremental ML Model Training Algorithm to Create Self-Learning IoT Devices'

BSP and examples to integrate the SparkFun TensorFlow board with the AmbiqSuite

Distributed Volunteer Computing with IOT

Mobilenet v1 (3,128,128, alpha=0.25) on STMH7 using STMCube AI

MicroAI™ is an AI engine that can operate on low power edge and endpoint devices. It can learn the pattern of any and all time series data and can be used to detect anomalies or abnormalities, make one step ahead predictions/forecasts, and calculate the remaining life of entities (whether it is industrial machinery, small devices or the like).

Collaborative Edge and Cloud Neural Networks for Real-Time Video Processing

Smart vending machine with non-contact interaction based on gesture recognition