A Photoelectric Spiking Neuron for Visual Depth Perception

Abstract

The biological visual system encodes optical information into spikes and processes them by the neural network, which enables the perception with high throughput of visual processing with ultralow energy budget. This has inspired a wide spectrum of devices to imitate such neural process, while precise mimicking such procedure is still highly required. Here, a highly bio‐realistic photoelectric spiking neuron for visual depth perception is presented. The firing spikes generated by the TaOX memristive spiking encoders have a biologically similar frequency range of 1–200 Hz and sub‐micro watts power. Such spiking encoder is integrated with a photodetector and a network of neuromorphic transistors, for information collection and recognition tasks, respectively. The distance‐dependent response and eye fatigue of biological visual systems have been mimicked based on such photoelectric spiking neuron. The simulated depth perception shows a recognition improvement by adapting to sights at different distances. The results can advance the technologies in bioinspired or robotic systems that may be endowed with depth perception and power efficiency at the same time.

Multiphotoconductance Levels of the Organic Semiconductor of Polyimide-Based Memristor Induced by Interface Charges

“…M emristors, featuring high nonlinearity, 1,2 low power consumption, 3,4 and continuously modulated conductance, 5,6 have made significant progress and breakthroughs ranging from memory-in logic, T-bit data storage, and bioinspired neuromorphic computing. 7−9 Memristive materials include three categories: oxides, 10,11 chalcogenides, 12,13 and organics. 14,15 Oxides compatible with CMOS as the mainstream switching layer have been extensively investigated for decades.…”

“…Memristors, featuring high nonlinearity, , low power consumption, , and continuously modulated conductance, , have made significant progress and breakthroughs ranging from memory-in logic, T-bit data storage, and bioinspired neuromorphic computing. − Memristive materials include three categories: oxides, , chalcogenides, , and organics. , Oxides compatible with CMOS as the mainstream switching layer have been extensively investigated for decades . In contrast to oxides, organics with tremendous varieties due to the millions of carbon, hydrogen, oxygen, and nitrogen compositions exhibit unique memristive synapse adjustability to faithfully mimic the neurological system’s function. , …”

Progress of Materials and Devices for Neuromorphic Vision Sensors

“…For collision avoidance, biological proximity recognition systems employ several strategies for estimating the approximate distance from an approaching object. In the case of a human vision system, the human eye perceives distances from objects using the binocular parallax principle [ 105 , 106 ]. As the eyes of humans are far apart from each other, the image coming into each eye will look slightly different.…”

An Oxide Based Spiking Thermoreceptor for Low-Power Thermography Edge Detection

“…T HE classical digital systems that rely on centralized and sequential operations suffer from severe energy issues and low robustness. While, the somatosensory system dependents on the distributed network of receptors, neurons, and synapses, enabling low-energy interaction with real-world [2]. What's more, it interprets the external stimuli into a representation of the external environment using a 'language' of spike, avoiding the drift and noise problems over a long transmission distance universally in a digital system [3], [4].…”

“…Inspired by the biological sensory processing paradigm, the artificial spiking receptor (ASR) has aroused extensive interesting recently [2], [3], [5], [6], [7], [8], [9], [10], [11]. For example, a spiking photoreceptor based on indium gallium zinc oxide (IGZO) has been proposed with the capability to convert UV light into a spike train at a rate dependent on the light wavelength.…”