Bioinspired artificial visual system based on 2D WSe₂ synapse array
Machine vision systems that capture images for visual inspection and recognition tasks must be able to perceive, memorize, and compute any color scene. To achieve this, most of the current visual systems use circuits and algorithms which may reduce efficiency and increase complexity. Herein, a 2D se...
| Main Authors: | , , , , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/170634 |
| _version_ | 1826118706558664704 |
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| author | Gong, Yue Xie, Peng Xing, Xuechao Lv, Ziyu Xie, Tao Zhu, Shirui Hsu, Hsiao-Hsuan Zhou, Ye Han, Su-Ting |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Gong, Yue Xie, Peng Xing, Xuechao Lv, Ziyu Xie, Tao Zhu, Shirui Hsu, Hsiao-Hsuan Zhou, Ye Han, Su-Ting |
| author_sort | Gong, Yue |
| collection | NTU |
| description | Machine vision systems that capture images for visual inspection and recognition tasks must be able to perceive, memorize, and compute any color scene. To achieve this, most of the current visual systems use circuits and algorithms which may reduce efficiency and increase complexity. Herein, a 2D semiconductor tungsten diselenide (WSe2)-based phototransistor that successfully demonstrates an artificial vision system integrating the processing capability of visual information sensing memory, is reported. Furthermore, based on a 6 × 6 fabricated retinal perception array, artificial visual information sensing memory and processing system are proposed to perform image recognition tasks, which can avoid the time delay and energy consumption caused by data conversion and movement. On the other hand, highly linear symmetric synaptic plasticity can be achieved based on the modulation of carrier types in WSe2 transistors with different thicknesses, facilitating the high level of training and inference accuracy for artificial neural networks. Last, through training and inference simulations, the feasibility of the hybrid synapses for optical neural networks (ONN) is demonstrated. |
| first_indexed | 2024-10-01T04:47:50Z |
| format | Journal Article |
| id | ntu-10356/170634 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:47:50Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1706342023-09-25T01:54:57Z Bioinspired artificial visual system based on 2D WSe₂ synapse array Gong, Yue Xie, Peng Xing, Xuechao Lv, Ziyu Xie, Tao Zhu, Shirui Hsu, Hsiao-Hsuan Zhou, Ye Han, Su-Ting School of Electrical and Electronic Engineering School of Materials Science and Engineering Engineering::Materials Artificial Vision System In-sensor Computing Machine vision systems that capture images for visual inspection and recognition tasks must be able to perceive, memorize, and compute any color scene. To achieve this, most of the current visual systems use circuits and algorithms which may reduce efficiency and increase complexity. Herein, a 2D semiconductor tungsten diselenide (WSe2)-based phototransistor that successfully demonstrates an artificial vision system integrating the processing capability of visual information sensing memory, is reported. Furthermore, based on a 6 × 6 fabricated retinal perception array, artificial visual information sensing memory and processing system are proposed to perform image recognition tasks, which can avoid the time delay and energy consumption caused by data conversion and movement. On the other hand, highly linear symmetric synaptic plasticity can be achieved based on the modulation of carrier types in WSe2 transistors with different thicknesses, facilitating the high level of training and inference accuracy for artificial neural networks. Last, through training and inference simulations, the feasibility of the hybrid synapses for optical neural networks (ONN) is demonstrated. This research was supported by the NSFC Program (grant nos. 62122055, 62074104, 62104154, 61974093, and 62001307), the Guangdong Basic and Applied Basic Research Foundation (Grant Nos. 2023A1515012479 and 2021A1515012569), the Science and Technology Innovation Commission of Shenzhen (Grant Nos. RCYX20200714114524157, JCYJ20220818100206013, and 20210324095207020), and the NTUT-SZU Joint Research Program. 2023-09-25T01:54:57Z 2023-09-25T01:54:57Z 2023 Journal Article Gong, Y., Xie, P., Xing, X., Lv, Z., Xie, T., Zhu, S., Hsu, H., Zhou, Y. & Han, S. (2023). Bioinspired artificial visual system based on 2D WSe₂ synapse array. Advanced Functional Materials. https://dx.doi.org/10.1002/adfm.202303539 1616-301X https://hdl.handle.net/10356/170634 10.1002/adfm.202303539 2-s2.0-85160801261 en Advanced Functional Materials © 2023 Wiley-VCH GmbH. All rights reserved. |
| spellingShingle | Engineering::Materials Artificial Vision System In-sensor Computing Gong, Yue Xie, Peng Xing, Xuechao Lv, Ziyu Xie, Tao Zhu, Shirui Hsu, Hsiao-Hsuan Zhou, Ye Han, Su-Ting Bioinspired artificial visual system based on 2D WSe₂ synapse array |
| title | Bioinspired artificial visual system based on 2D WSe₂ synapse array |
| title_full | Bioinspired artificial visual system based on 2D WSe₂ synapse array |
| title_fullStr | Bioinspired artificial visual system based on 2D WSe₂ synapse array |
| title_full_unstemmed | Bioinspired artificial visual system based on 2D WSe₂ synapse array |
| title_short | Bioinspired artificial visual system based on 2D WSe₂ synapse array |
| title_sort | bioinspired artificial visual system based on 2d wse₂ synapse array |
| topic | Engineering::Materials Artificial Vision System In-sensor Computing |
| url | https://hdl.handle.net/10356/170634 |
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