Review of state-of-the-art artificial compound eye imaging systems

Cheng, Yang; Cao, Jie; Zhang, Yangkun; Hao, Qun

doi:10.1088/1748-3190/aaffb5

Cited by 89 publications

(48 citation statements)

References 148 publications

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“…In the current artificial‐vision technology, state‐of‐the‐art imaging devices can efficiently detect images. [ 2 ] However, these systems generate a large amount of redundant dataset. [ 3,4 ] This requires significant computation to extract meaningful information and large data storage which are often provided by offloading data to the cloud and applying machine learning algorithms for processing.…”

Section: Figurementioning

confidence: 99%

Fully Light‐Controlled Memory and Neuromorphic Computation in Layered Black Phosphorus

et al. 2020

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Imprinting vision as memory is a core attribute of human cognitive learning. Fundamental to artificial intelligence systems are bioinspired neuromorphic vision components for the visible and invisible segments of the electromagnetic spectrum. Realization of a single imaging unit with a combination of in‐built memory and signal processing capability is imperative to deploy efficient brain‐like vision systems. However, the lack of a platform that can be fully controlled by light without the need to apply alternating polarity electric signals has hampered this technological advance. Here, a neuromorphic imaging element based on a fully light‐modulated 2D semiconductor in a simple reconfigurable phototransistor structure is presented. This standalone device exhibits inherent characteristics that enable neuromorphic image pre‐processing and recognition. Fundamentally, the unique photoresponse induced by oxidation‐related defects in 2D black phosphorus (BP) is exploited to achieve visual memory, wavelength‐selective multibit programming, and erasing functions, which allow in‐pixel image pre‐processing. Furthermore, all‐optically driven neuromorphic computation is demonstrated by machine learning to classify numbers and recognize images with an accuracy of over 90%. The devices provide a promising approach toward neurorobotics, human–machine interaction technologies, and scalable bionic systems with visual data storage/buffering and processing.

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Section: Figurementioning

confidence: 99%

Fully Light‐Controlled Memory and Neuromorphic Computation in Layered Black Phosphorus

et al. 2020

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“…model relies on strong spatial inhibitio units (Figure 2a). The presence of suc was investigated by quantifying the r moving in the presence of a distracte distances [34]. As the distracter target strong symmetrical surround, peak inh ated at ca.…”

Section: Target Detection Using Spatiot Dynamicsmentioning

confidence: 99%

“…1. In most insect species, vision is mediated by compound eyes in the first layer of Retina [98,34], which consists of photoreceptors capturing greyscale or single-channel (normally the green channel) images sequence. This neuropile layer retrieves motion information by spatial filtering of input signals at the ommatidia level [98], as shown in the LGMD models in the Fig.…”

Section: Similarities In Different Motion Perception Modelsmentioning

confidence: 99%

Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review

Wang

et al. 2019

Artificial Life

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Motion perception is a critical capability determining a variety of aspects of insects' life, including avoiding predators, foraging and so forth. A good number of motion detectors have been identified in the insects' visual pathways.Computational modelling of these motion detectors has not only been providing effective solutions to artificial intelligence, but also benefiting the understanding of complicated biological visual systems. These biological mechanisms through millions of years of evolutionary development will have formed solid modules for constructing dynamic vision systems for future intelligent machines. This article reviews the computational motion perception models originating from biological research of insects' visual systems in the literature. These motion perception models or neural networks comprise the looming sensitive neuronal models of lobula giant movement detectors (LGMDs) in locusts, the translation sensitive neural systems of direction selective neurons (DSNs) in fruit flies, bees and locusts, as well as the small target motion detectors (STMDs) in dragonflies and hover flies. We also review the applications of these models to robots and vehicles. Through these modelling studies, we summarise the methodologies that generate different direction and size selectivity in motion perception. At last, we discuss about multiple systems integration and hardware realisation of these bio-inspired motion perception models.

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“…At present, optical systems are developing in the direction of compact structures, integration, and large fields of view. Natural compound eyes have the characteristics of a large field of view, small size, and high sensitivity to moving objects [1]. Inspired by natural compound eyes, bionic artificial compound eyes have become a focused area of research in recent years.…”

Section: Introductionmentioning

confidence: 99%

Design and Integration of the Single-Lens Curved Multi-Focusing Compound Eye Camera

et al. 2021

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Compared with a traditional optical system, the single-lens curved compound eye imaging system has superior optical performance, such as a large field of view (FOV), small size, and high portability. However, defocus and low resolution hinder the further development of single-lens curved compound eye imaging systems. In this study, the design of a nonuniform curved compound eye with multiple focal lengths was used to solve the defocus problem. A two-step gas-assisted process, which was combined with photolithography, soft photolithography, and ultraviolet curing, was proposed for fabricating the ommatidia with a large numerical aperture precisely. Ommatidia with high resolution were fabricated and arranged in five rings. Based on the imaging experimental results, it was demonstrated that the high-resolution and small-volume single-lens curved compound eye imaging system has significant advantages in large-field imaging and rapid recognition.

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Review of state-of-the-art artificial compound eye imaging systems

Cited by 89 publications

References 148 publications

Fully Light‐Controlled Memory and Neuromorphic Computation in Layered Black Phosphorus

Fully Light‐Controlled Memory and Neuromorphic Computation in Layered Black Phosphorus

Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review

Design and Integration of the Single-Lens Curved Multi-Focusing Compound Eye Camera

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