Unsupervised Adaptive Multi-Object Tracking-by-Clustering Algorithm With a Bio-Inspired System

A problem of current interest is how to emulate nature by acquiring information in a neuromorphic-like fashion; namely, by using configurable hardware and electronic systems to emulate the information gathering and processing strategies of biological systems. In this paper, we introduce BioCAMSHIFT,...

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Veröffentlicht in:	IEEE access 2022, Vol.10, p.24895-24908
Hauptverfasser:	Guillen-Garcia, Julio, Palacios-Alonso, Daniel, Cabello, Enrique, Conde, Cristina
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive algorithms address-event representation (AER) Algorithms bio-inspired system BioCAMSHIFT bioinformatics CAMSHIFT Clustering Clustering algorithms Communications systems Electronic systems Field of view jAER Multiple target tracking neuromorphic system Neuromorphics Neurons Protocols Retina Robot sensing systems Silicon silicon retina devices
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