STM32 MCUs Machine learning & AI

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Edge AI for all. NanoEdge AI Studio autoML tool, now free for STM32 and open to all ARM Cortex-M bas

NanoEdge AI Studio v4.3 is now offered for free to all engineers, giving them the opportunity to create highly efficient TinyML libraries that can be deployed on Cortex-M based microcontrollers. In addition, other enhancements have been integrated to...

ST30449_nanoedge-ai-studio-motor (2).jpg ST30449_nanoedge-ai-studio-motor (2).jpg

Stateful LSTMs

When importing a Keras LSTM model, the stateful=True parameter seems to be ignored by Cube.AI, resulting in a state reset after every prediction. Is it somehow possible to prevent this state reset in Cube.AI, so that the model can actually be used in...

EPelz by Associate II
  • 1 replies
  • 4 kudos

Missing ai_platform.h and bsp_ai.h?

Not be able to compile as it asks for ai_platform.h? But the file exists: Middlewares/ST/AI/AI/include/ai_platform.hCopied into teh Inc folder but then I got this bps_ai.h is not found.I am using NUCLEO_H743ZI on Mac.Any suggestions?Thank you in adva...

NMoom by Associate
  • 5 replies
  • 1 kudos

INTERNAL ERROR (Stm32com Exception)

Hello,I am currently using X-CUBE-AI library to run neural networks on a stm32h747. I successfully generated and validated on board single input and output networks, but when I execute the validation through CLI with a multi output network, I get an ...

Unable to load asc_keras_mod_93_int8.tflite from FP-AI-SENSING-1 using various tensorflow versions in python. Error message: ValueError: quantized_dimension must be in range [0, 1). Was 3.

Hello,I am currently working with the acoustic scene classification (ASC) of the FP-AI-SENSING1 project.I tried to load the tflite model, which is provided at: STM32CubeFunctionPack_SENSING1_V4.0.2\Utilities\AI_Ressources\models\asc_keras_mod_93_int8...

Ilkay1 by Associate
  • 1 replies
  • 0 kudos