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Lorenzo Rizzello

Lorenzo Rizzello is an embedded software engineer at Skypersonic, a young company manufacturing drones for indoor inspections. He enjoys programming microcontrollers to control and locate aerial vehicles in GPS-denied environments. Lorenzo also has experience developing firmware in Python for MCU's using platforms like Zerynth which target IoT applications. He has been collaborating with Jacob Beningo on Python-based environments for Machine Learning applications on resource-constrained devices such as OpenMV. Lorenzo holds a Master's degree in Robotics and Automation Engineering from the University of Pisa.

Object Classification Techniques using the OpenMV Cam H7

Machine Learning for embedded systems has recently started to make sense: on-device inference reduces latency, costs and minimizes power consumption compared to cloud-based solutions. Thanks to Google TFLite Micro, and its optimized ARM CMSIS NN kernel, on-device inference now also means microcontrollers such as ARM Cortex-M processors.

In this session, we will examine machine vision examples running on the small and power-efficient OpenMV H7 camera. Attendees will learn what it takes to train models with popular desktop Machine Learning frameworks and deploy them to a microcontroller. We will take a hands-on approach, using the OpenMV camera to run the inference and detect objects placed in front of the camera.

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