New Deep Learning Anomaly Detection Available From Swedish Firm

By Joel Davies -

Imagimob has released a new version of the tinyML platform Imagimob AI to support end-to-end development of deep learning anomaly detection.

Imagimob is a Swedish developer of technology for real-time artificial intelligence on the edge. Imagimob AI is the company’s development platform for machine learning on edge devices which allows users to go from data collection to deployment on an edge device in minutes.

The new anomaly detection features include end-to-end training and deployment of convolutional autoencoder networks for anomaly detection/predictive maintenance and an anomaly detection starter-project for rotating machinery to get developers up and running.

Following the new release, the company stated: “A big strength with deep learning anomaly detection is that it delivers high performance as well as eliminates the need for feature engineering, thus saving costs and reducing time-to-market. Not only is deep learning anomaly detection better for eliminating the need for feature engineering but it can also leverage and deliver excellent performance on the new generation of powerful neural network processors that is now hitting the market. This means that when going to the edge customers can make the most of their hardware”.

Feature engineering is the act of converting raw observations into desired features using statistical or mathematical functions. Feature engineering normally requires domain expertise and can be time-consuming. With the added support for autoencoder networks in Imagimob AI, developers can build anomaly detection in less time, and with better performance.

Other improvements the company notes are:

  • Support for quantization of models in the graphical user interface. This includes quantized models, reducing model size and decreasing inference time on MCUs without an FPU
  • Improved model prediction – tracking of how models perform with millisecond resolution, before deploying given different confidence thresholds
  • Faster training and model evaluation
  • Increased support for large data sets
  • Starter project for Renesas RA2L1 – Capacitive Touch Sensing Unit
  • In total 8 starter projects, supporting sensors and MCU’s from Texas Instruments, Renesas, STMicroelectronics, Acconeer and Nordic Semiconductors

The anomaly detection solution from Imagimob has been tested and verified on real-world machine and sensor data. The new version of Imagimob AI was released on February 28th and is available for a free trial.

You can find more information about Imagimob and Imagimob AI on its website.

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