AITS Journal
Published in

AITS Journal

Bringing ONNX Models to MicroControllers, IoT and Edge Devices

on-device AI applications running on battery without internet connectivity are gaining ground primarily because of low power, low latency and enhanced privacy benefits. Deploying AI models on the microcontrollers (aka MCUs), IoT or edge device is a tough proposition. Complexities range from developing right model, choosing right framework, model conversion, to identifying the right MCU to fit the use case, etc.

Open Neural Network Exchange (ONNX) is an open standard format for representing machine learning models.

--

--

--

AI content from AITS associates with 💝. AITS is a deep learning company and lead developer of open source deep learning compiler.

Recommended from Medium

How To Prepare Text Data for Natural Language Processing (NLP)

Typewriter keyboard

Jigsaw Unintended Bias in Toxicity Classification

Optimizing Alimama’s Digital Marketing Solution with MaxCompute’s Advanced Features

Deep Learning and Portfolio Management

Summaries big text with a seq2seq Network and Attention

Markov chains and Markov Decision process

Testing a Chatbot with k-folds Cross Validation

Cooking with Computer Vision

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Rohit Sharma

Rohit Sharma

🏢 ai-techsystems.com | 🕊@srohit | 🔗 linkedin.com/in/srohit0 | ❔Quora: qr.ae/TWGSt9 | 💻 Github: srohit0.github.io

More from Medium

CNN Model for Self-Driving Cars

What is Iran? (machine translation) | GEOFOR | Geopolitical forecast

Danfo Chronicles.