Research Area

  • Title:
    Embedded Artificial Intelligence

  • Keywords:

    Embedded Sytems, TinyML, EdgeAI, CNN, DQNN

  • Description:
    This research aims to:
    • develop tiny machine learning (tinyML) algorithms and compressed deep neural networks (DNNs) in order to integrate such methods directly on the embedded devices (edgeAI) and micro-controller units (MCUs)
    • develop deeply quantized learning algorithms (DQNN) and associatedapplications targeting MCUs.develop artificial intelligence algorithms based on deep learning and computer
    • vision for Advanced Driver Assistance Systems (ADAS).
    • develop intelligent embedded systems for smart agriculture, based on deep learning techniques applied to images.
  • Laboratory:

    Embedded Systems and Artificial Intelligence Lab

  • Contact Person:

    Laura Falaschetti

  • Collaborations:

    STMicroelectronics, System Research and Applications, Agrate Brianza