Edge AI

[webinar - Program decision trees in sensors with a Machine Learning Core]

 [webinar - Program decision trees in sensors with a Machine Learning Core]

[webinar - Program decision trees in sensors with a Machine Learning Core]

[webinar - Program decision trees in sensors with a Machine Learning Core]

[webinar - Program decision trees in sensors with a Machine Learning Core]

[webinar - Program decision trees in sensors with a Machine Learning Core]

[webinar - Program decision trees in sensors with a Machine Learning Core]

[webinar - Program decision trees in sensors with a Machine Learning Core]

[webinar - Program decision trees in sensors with a Machine Learning Core]

[webinar - Program decision trees in sensors with a Machine Learning Core]

 [webinar - Program decision trees in sensors with a Machine Learning Core]

 [webinar - Program decision trees in sensors with a Machine Learning Core]

 [webinar - Program decision trees in sensors with a Machine Learning Core]

[webinar - Program decision trees in sensors with a Machine Learning Core]

 [webinar - Program decision trees in sensors with a Machine Learning Core]

[webinar - Program decision trees in sensors with a Machine Learning Core]

 [webinar - Program decision trees in sensors with a Machine Learning Core]

 [webinar - Program decision trees in sensors with a Machine Learning Core]

[webinar - Program decision trees in sensors with a Machine Learning Core]

 [webinar - Program decision trees in sensors with a Machine Learning Core]

Good afternoon everyone,I am currently working on a predictive maintenance projet using vibration classification with the MLC of a LSM6DSOX.I would like to try using several decision tree at the same time (with a maximum of 8 according to the datasheet), 3 for example.I have some trouble to build my .ucf file.I tried to do exactly the same than with a single decision tree, but it does not work.Actually I can build it the .ucf file, but I am getting "0x00" (default value) output in every channels of my MLC, whereas it should not be possible with the configuration I made.So I think I made a mistake during the configuration step on Unico, but I cannot see it.Maybe there are requirements I did not follow, or I may have to change my MLC configuration ...Is there any tutorial that explain how to configure the MLC with several decision tree ? Or can anyone explain me my possible mistake ? Thank you,Have a nice day,Julien.

I have a simple binary classification ANN model built with Tensorflow Keras and converted as Tensorflowlite model. This model gets imported and analyzed on the cubeMX tool without any errors. There is no IO input required for this trial model, so allowing random numbers for input features. Without any modifications to the code imported to STM32CubeIDE and build succeeds. While debugging, i can see that inside MX_X_CUBE_AI_Process() --> aiRun() method is returning error code 23 and error Type as 18. Since the analyze function succeeded during code generation process, i expected that this code runs without any modification. Any suggestions please?

It is now available a section of the Community page dedicated to New Ideas (LINK). This new "zone" is intended for ST products' users to give the Community technical feedback on available product areas.MEMS&Sensors community group has especially a couple of pages dedicated to the MEMS Machine Learning & AI ("X-factor products") and SensorTile.box reference tool:Further details HERE and below �?�

I am new to STM32 and wants to implement a neural network application on  STM32H743ZI. Please provide me some guide lines

Hi,STM32L5 has Cortex-M33 processor. In the official documentation it says that Cube.AI supports Cortex-M CPUs (including M33). Why is it still not possible to choose AI library for Cortex-M33 on STMCubeMX IDE? Is there anything fundamentally different that there is no support? Regards,SK