Model ST MNIST
Input size: 28x28x1
Memory footprint:
Float model:
38 Kbytes of flash memory for weights
30 Kbytes ofRAM for activations
Quantized model:
10 Kbytes of flash memory for weights
14 Kbytes ofRAM for activations
Accuracy:
Float model: 93.48%
Quantized model: 93.39%
Performance on STM32L562E @ 110 MHz
Float model:
Inference time: 83 ms
Frame rate: 12 fps
Quantized model:
Inference time: 29 ms
Frame rate: 34 fps
Confusion matrix
A collection of reference AI models optimized to run on ST devices with associated deployment scripts. The model zoo is a valuable resource to add edge AI capabilities to embedded applications.
A free STM32Cube expansion package, X-CUBE-AI allows developers to convert pretrained AI algorithms automatically, such as neural network and machine learning models, into optimized C code for STM32.
The STM32 family of 32-bit microcontrollers based on the Arm Cortex®-M processor is designed to offer new degrees of freedom to MCU users. It offers products combining very high performance, real-time capabilities, digital signal processing, low-power / low-voltage operation, and connectivity, while maintaining full integration and ease of development.