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Title: Wi-Fi based user identification using in-air handwritten signature
Authors: Jung, Junsik
Moon, Han-Cheol
Kim, Jooyoung
Kim, Donghyun
Toh, Kar-Ann
Keywords: Engineering::Computer science and engineering
Issue Date: 2021
Source: Jung, J., Moon, H., Kim, J., Kim, D. & Toh, K. (2021). Wi-Fi based user identification using in-air handwritten signature. IEEE Access, 9, 53548-53565.
Journal: IEEE Access
Abstract: This paper conducts a feasibility study regarding the use of the Wi-Fi channel state information for user recognition based on in-air handwritten signatures. A novel system for identity recognition is thus proposed to observe for distinctive signal distortions along the propagation path for different users. The system capitalizes on the vast availability of Wi-Fi signals for signal analysis without needing additional hardware infra-structure. Since the patterns of the raw Wi-Fi signals are sensitive to the signer's location, a transfer learning has been adopted to cope with the positional variation. Specifically, features trained at one position are transferred to classify signals collected at another position via a single shot retraining. A kernel and range space projection has been adopted for the single shot retraining. Our experiments show encouraging results for the proposed system.
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2021.3071228
Rights: © 2021 IEEE. This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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