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New Neuromorphic AI NM500 and Its ADAS Application

  • Jungyun KimEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 554)

Abstract

This article deals with an ADAS (Advanced Driver Assistance System) application using newly developed neuromorphic artificial intelligent chip NM500. Neuromorphic artificial intelligence is distinguished from other AI by its particular hardware structure and parallel algorithms of learning and recognition. Thus, neurons of NM500 can learn and recognize patterns extracted from any data sources with less energy and complexity than modern microprocessors. The proposed application can control the vehicle speed by recognizing the traffic information images marked on road. We have built a small-scaled vehicle model to discuss the real-time performance as well as hardware implementation with NM500. Taking advantages of NM500, the system simply consists of a low-priced surveillance camera attached in the front windshield of a vehicle and an Arduino kit, which processes the video signal from the camera and speed control signal.

Keywords

NM500 Neuromorphic chip Artificial intelligence Edge computing ADAS application 

Notes

Acknowledgement

This work was supported by research grants from the Catholic University of Daegu in 2017.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.School of Mechanical and Automotive EngineeringCatholic University of DaeguGyeongsan-siKorea

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