DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Inkyu | ko |
dc.date.accessioned | 2023-09-07T06:00:40Z | - |
dc.date.available | 2023-09-07T06:00:40Z | - |
dc.date.created | 2023-09-07 | - |
dc.date.issued | 2021-12-11 | - |
dc.identifier.citation | 2021 IEEE International Electron Devices Meeting (IEDM) | - |
dc.identifier.issn | 2380-9248 | - |
dc.identifier.uri | http://hdl.handle.net/10203/312310 | - |
dc.description.abstract | Microfabricated MEMS devices and functional nanomaterials can enable low-power and self-powered gas sensors for the internet-of-Things (IoT) applications. In this paper, various low-power / self-powered gas sensors and deep learning-based sensor signal processing technologies developed by our research group are presented. | - |
dc.language | English | - |
dc.publisher | IEEE | - |
dc.title | Low-power and Self-powered Environmental Sensor Assisted by Deep-Learning Technology | - |
dc.type | Conference | - |
dc.identifier.wosid | 000812325400037 | - |
dc.identifier.scopusid | 2-s2.0-85126971879 | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | 2021 IEEE International Electron Devices Meeting (IEDM) | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | San Francisco, CA | - |
dc.identifier.doi | 10.1109/iedm19574.2021.9720532 | - |
dc.contributor.localauthor | Park, Inkyu | - |
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