Software Update Release Notes

Qeexo AutoML 1.11.3

December 16, 2020

New Features

  • Added new machine learning models: Polynomial Support Vector Machine (POLYSVM), RBF Support Vector Machine (RBFSVM), Gaussian Naive Bayes (GNB), One Class Random Forest (ORF).

  • Added optional step to collect and upload Test Data datasets to measure trained model performance against the uploaded datasets.

  • Added PCA plot and F1 score to model details.

  • Added time limit and trial threshold to Hyperparameter Tuning Optimizer.

Bug Fixes & Improvements

  • Removed Chrome extension dependency by adding a Qeexo AutoML native app.

  • STWIN now supports both digital and analog microphones.

  • Added proxy server option for Qeexo AutoML installers to bypass network restrictions.

Known Issues

  • Multiple CSV files upload with different sensor configurations is not supported and may lead to unexpected issues. Each upload should only contain data with the same sensor configurations.

  • Uploading a large amount of data through multiple CSV files at once may fail when server traffic overloads.

Additional notes

  • SensorTile.Box now supports DFU mode, without the need for ST-LINK/v2.

Previous Releases

Qeexo AutoML 1.10.3

September 24, 2020

New Features

• Added new hardware platform: Arduino Nano 33 IoT, featuring an Arm Cortex-M0+ MCU.
• Renesas RA6M3 ML Sensor Module now supports live classification over Bluetooth.
• Bronze users who are using the Arduino Nano 33 BLE Sense can now create custom applications by downloading machine learning models as statically-linked libraries.

Bug Fixes & Improvements

• Fixed training failures of the CNN model under certain specific configurations.
• Fixed re-recording so that original data will be properly overwritten.

Known Issues

• Selecting data from the 1 Hz low-power accelerometer sensor from the STWINKT1 hardware sometimes causes training failures.
• Certain USB Type-C hubs cause connection issues in macOS.

Tips

• Use an USB A-to-C adapter rather than a hub to minimize connection issues if using macOS.
• If hardware is not behaving as expected, try disconnecting and reconnecting the USB cable and retry.

Qeexo AutoML 1.9.1

September 5, 2020

New Features

  • Added new hardware platform: RA6M3 ML Sensor Module from Renesas. Currently, accelerometer, gyroscope, humidity, light, and temperature sensors are supported.

  • Improved Qeexo AutoML sign up process.

  • Added DFU mode support for ST SensorTile.box, which means that the ST-LINK/v2 device programmer and adapter are no longer required to flash firmware on this hardware platformthe SensorTile.box.

Bug Fixes & Improvements

  • Fixed latency calculation failures.
  • Added various UI-related fixes/improvements.

Known Issues

  • Specific configurations of multiple sensors when selected together with the microphone, sometimes causes training failures of the CNN model.

  • Selecting data from the 1Hz Accelerometer lLow-power accelerometer sensor from STWINKT1 hardware sometimes causes training failures.

  • Sometimes, the original data would still exists after re-recording.

  • Class label names cannot contain special characters such as <, >, |, :, “, and \ .

  • Certain USB Type-C hubs cause connection issues in macOS. We recommend using an USB A-to-C adapter rather than a hub.

Qeexo AutoML 1.8.2

August 10, 2020

New Features

  • Added new hardware platform: STWINKT1 from STMicroelectronics.
  • Added new ML algorithms: one class SVM, linear SVM, RNN, CRNN.
  • Added Live Classification Analysis to finetune trained models.
  • Added quantization options to reduce model size.

Bug Fixes & Improvements

  • Fixed a flashing issue on the Arduino Nano 33 BLE Sense.
  • Fixed a training issue that occurs when only one axis (x, y, or z) is selected for accelerometer and/or gyroscope.
  • Added data-check-related improvements.
  • Added various UI-related fixes/improvements.

Known Issues

  • When different data types (Continuous/Event) are grouped together during training, unexpected results such as training failure may occur. We recommend not mixing different data types within a Group.
  • Specific configurations of multiple sensors when selected together with the microphone, sometimes causes training failures of the CNN model.
  • Class label names cannot contain special characters such as <, >, |, :, “, and \ .
  • Certain USB Type-C hubs cause connection issues in macOS. We recommend using an USB A-to-C adapter rather than a hub.

Thanks for the update!

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