Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/109142
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dc.contributorDepartment of Applied Physics-
dc.creatorHuang, PY-
dc.creatorJiang, BY-
dc.creatorChen, HJ-
dc.creatorXu, JY-
dc.creatorWang, K-
dc.creatorZhu, CY-
dc.creatorHu, XY-
dc.creatorLi, D-
dc.creatorZhen, L-
dc.creatorZhou, FC-
dc.creatorQin, JK-
dc.creatorXu, CY-
dc.date.accessioned2024-09-19T03:13:35Z-
dc.date.available2024-09-19T03:13:35Z-
dc.identifier.urihttp://hdl.handle.net/10397/109142-
dc.language.isoenen_US
dc.publisherNature Publishing Groupen_US
dc.rights© The Author(s) 2023en_US
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.rightsThe following publication Huang, PY., Jiang, BY., Chen, HJ. et al. Neuro-inspired optical sensor array for high-accuracy static image recognition and dynamic trace extraction. Nat Commun 14, 6736 (2023) is available at https://doi.org/10.1038/s41467-023-42488-9.en_US
dc.titleNeuro-inspired optical sensor array for high-accuracy static image recognition and dynamic trace extractionen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume14-
dc.identifier.doi10.1038/s41467-023-42488-9-
dcterms.abstractNeuro-inspired vision systems hold great promise to address the growing demands of mass data processing for edge computing, a distributed framework that brings computation and data storage closer to the sources of data. In addition to the capability of static image sensing and processing, the hardware implementation of a neuro-inspired vision system also requires the fulfilment of detecting and recognizing moving targets. Here, we demonstrated a neuro-inspired optical sensor based on two-dimensional NbS2/MoS2 hybrid films, which featured remarkable photo-induced conductance plasticity and low electrical energy consumption. A neuro-inspired optical sensor array with 10 × 10 NbS2/MoS2 phototransistors enabled highly integrated functions of sensing, memory, and contrast enhancement capabilities for static images, which benefits convolutional neural network (CNN) with a high image recognition accuracy. More importantly, in-sensor trajectory registration of moving light spots was experimentally implemented such that the post-processing could yield a high restoration accuracy. Our neuro-inspired optical sensor array could provide a fascinating platform for the implementation of high-performance artificial vision systems.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationNature communications, 2023, v. 14, 6736-
dcterms.isPartOfNature communications-
dcterms.issued2023-
dc.identifier.scopus2-s2.0-85174601436-
dc.identifier.eissn2041-1723-
dc.identifier.artn6736-
dc.description.validate202409 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China; National Key R&D Program of China; Natural Science Foundation of Guangdong Province; Young Innovative Talent Project Research Program of Guangdong Province; Shenzhen Science and Technology Programen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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