Unconventional machine learning for event-based sensors

Guido Zarrella

doi:10.1117/12.2677916

4 October 2023 Unconventional machine learning for event-based sensors

Guido Zarrella

Proceedings Volume 12693, Unconventional Imaging, Sensing, and Adaptive Optics 2023; 126930Z (2023) https://doi.org/10.1117/12.2677916
Event: SPIE Optical Engineering + Applications, 2023, San Diego, California, United States

Abstract

Event-based sensors represent an alternative paradigm in machine vision. As the commercial hardware ecosystem undergoes rapid maturation, the machine learning community is racing to unlock new opportunities which exploit these devices’ unique combination of microsecond-scale sampling, low data rates, and extreme dynamic range. This talk will cover recent advances in unconventional machine vision algorithms for these unconventional sensors, and highlights the need for the open source community to develop new benchmark tasks that accurately quantify the value of unconventional devices relative to traditional focal plane arrays.

Conference Presentation

Citation Download Citation

Guido Zarrella "Unconventional machine learning for event-based sensors", Proc. SPIE 12693, Unconventional Imaging, Sensing, and Adaptive Optics 2023, 126930Z (4 October 2023); https://doi.org/10.1117/12.2677916

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