Image Sensor System With Bio-Inspired Efficient Coding and Adaptation

Okuno, Hirotsugu; Yagi, T.

doi:10.1109/tbcas.2012.2185048

Cited by 13 publications

(2 citation statements)

References 31 publications

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“…The outer unit is composed of the silicon retina system with image-processing circuit (see Refs. [23], [24], [25], [26]) and a wireless communication unit to exchange data with the inner unit. The silicon retina system in Ref.…”

Section: Targeted Artificial Vision Systemsmentioning

confidence: 99%

“…The silicon retina system in Ref. [26] can perform high-speed image processing, which mimics the human retina with analog CMOS integrated circuits, and it generates stimulation data, which consists of stimuli strength, stimuli timing, and stimuli position. Figure 1 (a) shows an example of an input image from a silicon retina system, and Fig.…”

Section: Targeted Artificial Vision Systemsmentioning

confidence: 99%

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A Low-Energy Application Specific Instruction-Set Processor towards a Low-Computational Lossless Compression Method for Stimuli Position Data of Artificial Vision Systems

Sugiura

Imai

et al. 2017

Journal of Information Processing

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This paper proposes a novel data compression method for artificial vision systems and its low-energy implementation in order to reduce energy consumption in a wireless communication subsystem. The artificial vision systems are one of the methods for realizing visual prosthesis by controlling stimulus to visual nerves, and they consist of an inner stimulating unit and an outer image processing unit. The outer unit transmits information regarding stimulation to the inner unit via wireless communication, which occupies a large portion of the whole energy consumption. Reducing traffic in wireless communication is important to prevent damage caused by extra heat dissipation of the inner unit, which leads to excess energy consumption. The proposed compression method marks a higher compression ratio than the conventional compression methods by taking advantage of the analyses of stimuli position data, which is dominant in traffic. The proposed method is implemented as an application-domain specific instruction-set processor to achieve both configurability of stimulation control and compression efficiency. The evaluation results show that the proposed implementation reduces energy consumption by about 87% and 62% in the compression and decompression process, respectively. These results indicate that the proposed method can expect to reduce energy consumption in a wireless communication receiver dramatically.

show abstract

Section: Targeted Artificial Vision Systemsmentioning

confidence: 99%

Section: Targeted Artificial Vision Systemsmentioning

confidence: 99%

A Low-Energy Application Specific Instruction-Set Processor towards a Low-Computational Lossless Compression Method for Stimuli Position Data of Artificial Vision Systems

Sugiura

Imai

et al. 2017

Journal of Information Processing

View full text Add to dashboard Cite

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Event‐Based Neuromorphic Systems

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Mimicking Sensory Adaptation with Dielectric Engineered Organic Transistors

Shen

Jin

et al. 2019

Advanced Materials

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Mimicking sensory adaptation with transistors is essential for developing next‐generation smart circuits. A key challenge is how to obtain controllable and reversible short‐term signal decay while simultaneously maintaining long‐term electrical stability. By introducing a buried dynamic‐trapping interface within the dielectric layer, an organic adaptive transistor (OAT) with sensory adaptation functionality is developed. The device induces self‐adaptive interfacial trapping to enable volatile shielding of the gating field, thereby leading to rapid and temporary carrier concentration decay in the conductive channel without diminishing the mobility upon a fixed voltage bias. More importantly, the device exhibits a fine‐tuned decay constant ranging from 50 ms to 5 s, accurately matching the adaptation timescales in bio‐systems. This not only suggests promising applications of OATs in flexible artificial intelligent elements, but also provides a strategy for engineering organic devices toward novel biomimetic functions.

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Image Sensor System With Bio-Inspired Efficient Coding and Adaptation

Cited by 13 publications

References 31 publications

A Low-Energy Application Specific Instruction-Set Processor towards a Low-Computational Lossless Compression Method for Stimuli Position Data of Artificial Vision Systems

A Low-Energy Application Specific Instruction-Set Processor towards a Low-Computational Lossless Compression Method for Stimuli Position Data of Artificial Vision Systems

Hardware Infrastructure

Mimicking Sensory Adaptation with Dielectric Engineered Organic Transistors

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