Bioinspired in-sensor visual adaptation for accurate perception

被引:349
|
作者
Liao, Fuyou [1 ,2 ]
Zhou, Zheng [3 ]
Kim, Beom Jin [4 ]
Chen, Jiewei [1 ,2 ]
Wang, Jingli [1 ,2 ,5 ]
Wan, Tianqing [2 ]
Zhou, Yue [2 ]
Hoang, Anh Tuan [4 ]
Wang, Cong [1 ,2 ]
Kang, Jinfeng [3 ]
Ahn, Jong-Hyun [4 ]
Chai, Yang [1 ,2 ,6 ]
机构
[1] Hong Kong Polytech Univ Shenzhen Res Inst, Shenzhen, Peoples R China
[2] Hong Kong Polytech Univ, Dept Appl Phys, Hong Kong, Peoples R China
[3] Peking Univ, Inst Microelect, Beijing, Peoples R China
[4] Yonsei Univ, Sch Elect & Elect Engn, Seoul, South Korea
[5] Fudan Univ, Frontier Inst Chip & Syst, Shanghai, Peoples R China
[6] Hong Kong Polytech Univ, Res Inst Intelligent Wearable Syst, Hong Kong, Peoples R China
基金
中国博士后科学基金; 新加坡国家研究基金会;
关键词
MOS2; PHOTODETECTORS; ELECTRONICS;
D O I
10.1038/s41928-022-00713-1
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Charge trapping mechanisms in molybdenum-disulfide-based transistors can be used to mimic the adaptive behaviour of human eyes, allowing vision sensors to be created with high dynamic range. Machine vision systems that capture images for visual inspection and identification tasks have to be able to perceive a scene under a range of illumination conditions. To achieve this, current systems use circuitry and algorithms that compromise efficiency and increase complexity. Here we report bioinspired vision sensors that are based on molybdenum disulfide phototransistors and exhibit time-varying activation and inhibition characteristics. Charge trap states are intentionally introduced into the surface of molybdenum disulfide, enabling the dynamic modulation of the photosensitivity of the devices under different lighting conditions. The light-intensity-dependent characteristics of the sensors match Weber's law in which the perceived change in stimuli is proportional to the light stimuli. The approach offers visual adaptation with highly localized and dynamic modulation of photosensitivity under different lighting conditions at the pixel level, creating an effective perception range of up to 199 dB. The phototransistor arrays exhibit image contrast enhancement for both scotopic and photopic adaptation.
引用
收藏
页码:84 / 91
页数:8
相关论文
共 50 条
  • [1] Bioinspired in-sensor visual adaptation for accurate perception
    Fuyou Liao
    Zheng Zhou
    Beom Jin Kim
    Jiewei Chen
    Jingli Wang
    Tianqing Wan
    Yue Zhou
    Anh Tuan Hoang
    Cong Wang
    Jinfeng Kang
    Jong-Hyun Ahn
    Yang Chai
    Nature Electronics, 2022, 5 : 84 - 91
  • [2] In-Sensor Visual Perception and Inference
    Liu, Yanan
    Fan, Rui
    Guo, Jianglong
    Ni, Hepeng
    Bhutta, Muhammad Usman Maqboo
    Intelligent Computing, 2023, 2
  • [3] Optoelectronic graded neurons for bioinspired in-sensor motion perception
    Jiewei Chen
    Zheng Zhou
    Beom Jin Kim
    Yue Zhou
    Zhaoqing Wang
    Tianqing Wan
    Jianmin Yan
    Jinfeng Kang
    Jong-Hyun Ahn
    Yang Chai
    Nature Nanotechnology, 2023, 18 : 882 - 888
  • [4] Optoelectronic graded neurons for bioinspired in-sensor motion perception
    Chen, Jiewei
    Zhou, Zheng
    Kim, Beom Jin
    Zhou, Yue
    Wang, Zhaoqing
    Wan, Tianqing
    Yan, Jianmin
    Kang, Jinfeng
    Ahn, Jong-Hyun
    Chai, Yang
    NATURE NANOTECHNOLOGY, 2023, 18 (08) : 882 - +
  • [5] In-sensor visual adaptation across the spectrum
    Wang, Fang
    Wang, Jin
    Xie, Runzhang
    Hu, Weida
    NATURE ELECTRONICS, 2024, 7 (08): : 634 - 635
  • [6] Bioinspired in-sensor spectral adaptation for perceiving spectrally distinctive features
    Ouyang, Bangsen
    Wang, Jialiang
    Zeng, Guang
    Yan, Jianmin
    Zhou, Yue
    Jiang, Xixi
    Shao, Bangjie
    Chai, Yang
    NATURE ELECTRONICS, 2024, 7 (08): : 705 - 713
  • [7] Bionic visual-audio photodetectors with in-sensor perception and preprocessing
    Fu, Jintao
    Nie, Changbin
    Sun, Feiying
    Li, Genglin
    Shi, Haofei
    Wei, Xingzhan
    SCIENCE ADVANCES, 2024, 10 (07)
  • [8] Bioinspired in-sensor vision processing network for action recognition
    Chem, Jiewei
    Zhou, Yue
    Ahn, Jong-Hyun
    Chai, Yang
    8TH IEEE ELECTRON DEVICES TECHNOLOGY & MANUFACTURING CONFERENCE, EDTM 2024, 2024, : 478 - 480
  • [9] Bioinspired In-Sensor Multimodal Fusion for Enhanced Spatial and Spatiotemporal Association
    Ma, Sijie
    Zhou, Yue
    Wan, Tianqing
    Ren, Qinqi
    Yan, Jianmin
    Fan, Lingwei
    Yuan, Huanmei
    Chan, Mansun
    Chai, Yang
    NANO LETTERS, 2024, 24 (23) : 7091 - 7099
  • [10] In-Sensor Computing with Visual-Tactile Perception Enabled by Mechano-Optical Artificial Synapse
    Guo, Jiaxing
    Guo, Feng
    Zhao, Huijun
    Yang, Hang
    Du, Xiaona
    Fan, Fei
    Liu, Weiwei
    Zhang, Yang
    Tu, Dong
    Hao, Jianhua
    ADVANCED MATERIALS, 2025,