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Inspired by how humans recognize noisy images and the flexible modulation on the timescale of ion dynamics inside an emerging memtransistor, a novel neuromorphic vision system is reported based on the ion\u2010modulated memtransistors. By controlling the ion\u2010doping processes under adequate stimuli strengths, both short\u2010term and long\u2010term ion dynamics can be utilized to deliver energy\u2010efficient data processing. When dealing with image reconstructions, the short\u2010term accumulation effect of the device can help filter noises in a set of received noisy images while enhancing the original pattern information. The increased contrast can help distinguish the actual contents. To demonstrate systematic performances with the reconfiguration of devices, the nonlinear relationship between channel conductance variation and the amplitude of gate pulses into the network\u2010level simulation is extracted. Also, with the nonvolatile conductance change characteristic, the task of recognizing noisy images is performed to verify the versatility of ion\u2010modulated memtransistors in the neuromorphic artificial vision systems. An interactive preprint version of the article can be found here:\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/doi.org\/10.22541\/au.167939089.96499861\/v1\">https:\/\/doi.org\/10.22541\/au.167939089.96499861\/v1<\/jats:ext-link>\n                  <\/jats:p>","DOI":"10.1002\/aisy.202300026","type":"journal-article","created":{"date-parts":[[2023,4,26]],"date-time":"2023-04-26T22:57:58Z","timestamp":1682549878000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Neuromorphic Artificial Vision Systems Based on Reconfigurable Ion\u2010Modulated Memtransistors"],"prefix":"10.1002","volume":"5","author":[{"given":"Zhen","family":"Yang","sequence":"first","affiliation":[{"name":"Beijing Advanced Innovation Center for Integrated Circuits School of Integrated Circuits Peking University  Beijing 100871 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