Deploy Binarized Neural Networks (BNNs) AI on any Microcontroller Unit (MCU).
As an example, I deploy model inference on an STM32-F411CEU6 MCU, running at 100 MHz (0.1GHz). Using the MNIST dataset for numerical recognition classification tasks, the network utilizes an MLP architecture with a total of 7,890 parameters.
Each inference takes ONLY 1.3 ms, with an overall accuracy rate of 93.89%.
For training Binarized Neural Networks and automatically generating C code, please refer to the repository: https://github.com/ittuann/Binarized-Neural-Networks
