In this example, we have a Simulink model based on the shallow network with five layers described in Loren’s blog below for image classification using MNIST data:
We have three versions of the model – in double precision, single precision and a fixed-point version. These models can then be tested using live data from an Arduino Due using the Simulink® Support Package for Arduino® Hardware and deployed to the Arduino board as a standalone application.
The single precision and fixed-point versions were generated using Fixed-Point Designer as described in the links below. The fixed-point model uses no more than 16 bits and the accuracy of the model is above 94%.
MathWorks Fixed Point Team (2023). Image classification on an ARM Cortex M Microcontroller (https://www.mathworks.com/matlabcentral/fileexchange/68426-image-classification-on-an-arm-cortex-m-microcontroller), MATLAB Central File Exchange. 검색됨 .
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