A High-Speed Low-Cost VLSI System Capable of On-Chip Online Learning for Dynamic Vision Sensor Data Classification

This paper proposes a high-speed low-cost VLSI system capable of on-chip online learning for classifying address-event representation (AER) streams from dynamic vision sensor (DVS) retina chips. The proposed system executes a lightweight statistic algorithm based on simple binary features extracted...

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Detalles Bibliográficos

Principais autores:	Wei He, Jinguo Huang, Tengxiao Wang, Yingcheng Lin, Junxian He, Xichuan Zhou, Ping Li, Ying Wang, Nanjian Wu, Cong Shi
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2020-08-01
Series:	Sensors
Assuntos:	address-event representation (AER) Random Ferns object classification neuromorphic hardware online learning on-chip learning
Acceso en liña:	https://www.mdpi.com/1424-8220/20/17/4715
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