An Optoneuronic Device with Realistic Retinal Expressions for Bioinspired Machine Vision

Machine vision systems rely on communication between cameras and processor modules to capture and analyze visual information. This arrangement renders them as bulky and inefficient in terms of speed and power dissipation for futuristic big data applications that involve artificial intelligence algorithms. An apparatus able to imitate the operation of biologic eyes and function as a standalone platform would therefore present the next evolutional step in machine visual perception. Neuromorphic computing is an alternative approach to the Von Neumann architecture that carries the potential for implementing such intelligent cameras. In this regard, artificial synaptic devices have been widely used in recent years to construct hardware‐based neural networks mainly due to their adjustable electric parameters. Herein, a bioinspired, hybrid electrophotonic responsive neuronic device that mimics the combined functionality of retinal cones and bipolar cells is demonstrated. Under illumination, it features a hyperpolarization‐like current response in an OFF state and a complementary depolarized reaction when toggled to an ON state. Furthermore, electrical pulsing done in conjunction with light stimulation can emulate the horizontal cell neurotransmitter release in center‐surround biologic configurations. These devices may thus serve as building blocks for advanced visual systems, integrating self‐healing sensory and neuromorphic computing into an artificial cognitive retina.

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: An Optoneuronic Device with Realistic Retinal Expressions for Bioinspired Machine Vision ; volume:2 ; number:2 ; year:2020 ; extent:14 ; Advanced intelligent systems ; 2, Heft 2 (2020) (gesamt 14)

Beteiligte, Orts- und Zeitangaben

• Urheber: Berco, Dan ; Ang, Diing Shenp ; Zhang, Hai Zhong

Weitere Informationen

• DOI: 10.1002/aisy.201900115
• URN: urn:nbn:de:101:1-2022062909591862711050
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 15.08.2025, 07:35 MESZ