Imagimob AI, the First tinyML Platform to Support Deep Learning Anomaly Detection

By Tiera Oliver

Associate Editor

Embedded Computing Design

February 28, 2022

News

Imagimob AI, the First tinyML Platform to Support Deep Learning Anomaly Detection

Imagimob announced that its new release of the tinyML platform, Imagimob AI, supports end-to-end development of deep learning anomaly detection.

According to the company, with the added support for autoencoder networks in Imagimob AI, developers can now build anomaly detection in less time, and with better performance. Customers will be able to reduce development costs and shorten time to market.

The anomaly detection solution from Imagimob has been tested and verified on real-world machine and sensor data.

What's new in the latest Imagimob AI release

New anomaly detection features

  • End-to-end training and deployment of convolutional autoencoder networks for anomaly detection/predictive maintenance
  • Anomaly detection starter-project for rotating machinery to get developers up and running in minutes

Other improvements

  • 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 new release is available. Sign up for a free trial today. 

For more information, visit: https://www.mynewsdesk.com/imagimob/news/imagimob-ai-the-first-tinyml-platform-to-support-deep-learning-anomaly-detection-443070

Tiera Oliver, Associate Editor for Embedded Computing Design, is responsible for web content edits, product news, and constructing stories. She also assists with newsletter updates as well as contributing and editing content for ECD podcasts and the ECD YouTube channel. Before working at ECD, Tiera graduated from Northern Arizona University where she received her B.S. in journalism and political science and worked as a news reporter for the university’s student led newspaper, The Lumberjack.

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