Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385819626> ?p ?o ?g. }
- W4385819626 endingPage "12" @default.
- W4385819626 startingPage "1" @default.
- W4385819626 abstract "Advancements in sensing techniques have fueled the construction of a worldwide smart environment. An accompanying concern is the security issue. This paper presents a noninvasive user authentication technique using an ultra-wideband radar sensor. Human gait micro-Doppler signatures captured by the radar are used as the biometrics of individuals. Unlike the existing authentication techniques, our proposed method does not require a gallery set for retrieval during the testing stage. Instead, we formalize the authentication task as a one-class classification problem and utilize a generative adversarial network to characterize the legal users’ movement modes, especially the fine-grained distinctions of micro-Doppler signatures. Meanwhile, the discriminator automatically outputs the prediction result, indicating whether a user is legal or not. The fully convolutional network architecture and a fine-grained recognition module are added to enhance the discrimination ability of the model. Experiments are carried out using measurement data from 15 subjects, and the results demonstrate that the proposed method achieves an equal error rate of 0.234, outperforming the comparative algorithms by at least 9.8%. Moreover, the model is evaluated for its robustness against various attacks as well as different walking styles. An ablation study is conducted to verify the effectiveness of the network design." @default.
- W4385819626 created "2023-08-15" @default.
- W4385819626 creator A5015365860 @default.
- W4385819626 creator A5033072172 @default.
- W4385819626 creator A5034901041 @default.
- W4385819626 creator A5069988975 @default.
- W4385819626 date "2023-01-01" @default.
- W4385819626 modified "2023-10-16" @default.
- W4385819626 title "Radar-Based Noninvasive Person Authentication Using Micro-Doppler Signatures and Generative Adversarial Network" @default.
- W4385819626 cites W1122083611 @default.
- W4385819626 cites W1558778037 @default.
- W4385819626 cites W1560002189 @default.
- W4385819626 cites W1903029394 @default.
- W4385819626 cites W2009451935 @default.
- W4385819626 cites W2025768430 @default.
- W4385819626 cites W2050132334 @default.
- W4385819626 cites W2070381776 @default.
- W4385819626 cites W2075959322 @default.
- W4385819626 cites W2095038611 @default.
- W4385819626 cites W2102950522 @default.
- W4385819626 cites W2122538988 @default.
- W4385819626 cites W2128331885 @default.
- W4385819626 cites W2153594606 @default.
- W4385819626 cites W2157770256 @default.
- W4385819626 cites W2242223225 @default.
- W4385819626 cites W2344636067 @default.
- W4385819626 cites W2406349259 @default.
- W4385819626 cites W2599354622 @default.
- W4385819626 cites W2602548784 @default.
- W4385819626 cites W2790336835 @default.
- W4385819626 cites W2796289556 @default.
- W4385819626 cites W2798205579 @default.
- W4385819626 cites W2798365843 @default.
- W4385819626 cites W2887770386 @default.
- W4385819626 cites W2900466196 @default.
- W4385819626 cites W2904851779 @default.
- W4385819626 cites W2908400479 @default.
- W4385819626 cites W2914570111 @default.
- W4385819626 cites W2920322257 @default.
- W4385819626 cites W2942065897 @default.
- W4385819626 cites W2944320448 @default.
- W4385819626 cites W2952340467 @default.
- W4385819626 cites W2953842422 @default.
- W4385819626 cites W2954780117 @default.
- W4385819626 cites W2962823371 @default.
- W4385819626 cites W2963045681 @default.
- W4385819626 cites W2963049059 @default.
- W4385819626 cites W2963061824 @default.
- W4385819626 cites W2963073614 @default.
- W4385819626 cites W2964260849 @default.
- W4385819626 cites W2979978649 @default.
- W4385819626 cites W2988700451 @default.
- W4385819626 cites W2997725121 @default.
- W4385819626 cites W3003598450 @default.
- W4385819626 cites W3042239366 @default.
- W4385819626 cites W3096300328 @default.
- W4385819626 cites W3096831136 @default.
- W4385819626 cites W3104966193 @default.
- W4385819626 cites W3206370317 @default.
- W4385819626 cites W4205984557 @default.
- W4385819626 cites W4214482791 @default.
- W4385819626 cites W4294891471 @default.
- W4385819626 cites W4312302556 @default.
- W4385819626 cites W4312342130 @default.
- W4385819626 cites W4312363951 @default.
- W4385819626 cites W4312946738 @default.
- W4385819626 doi "https://doi.org/10.1109/tim.2023.3304683" @default.
- W4385819626 hasPublicationYear "2023" @default.
- W4385819626 type Work @default.
- W4385819626 citedByCount "0" @default.
- W4385819626 crossrefType "journal-article" @default.
- W4385819626 hasAuthorship W4385819626A5015365860 @default.
- W4385819626 hasAuthorship W4385819626A5033072172 @default.
- W4385819626 hasAuthorship W4385819626A5034901041 @default.
- W4385819626 hasAuthorship W4385819626A5069988975 @default.
- W4385819626 hasConcept C104317684 @default.
- W4385819626 hasConcept C108583219 @default.
- W4385819626 hasConcept C119857082 @default.
- W4385819626 hasConcept C124101348 @default.
- W4385819626 hasConcept C148417208 @default.
- W4385819626 hasConcept C153180895 @default.
- W4385819626 hasConcept C154945302 @default.
- W4385819626 hasConcept C184297639 @default.
- W4385819626 hasConcept C185592680 @default.
- W4385819626 hasConcept C2778559676 @default.
- W4385819626 hasConcept C2779803651 @default.
- W4385819626 hasConcept C38652104 @default.
- W4385819626 hasConcept C40969351 @default.
- W4385819626 hasConcept C41008148 @default.
- W4385819626 hasConcept C554190296 @default.
- W4385819626 hasConcept C55493867 @default.
- W4385819626 hasConcept C63479239 @default.
- W4385819626 hasConcept C76155785 @default.
- W4385819626 hasConcept C79403827 @default.
- W4385819626 hasConcept C81363708 @default.
- W4385819626 hasConcept C94915269 @default.
- W4385819626 hasConceptScore W4385819626C104317684 @default.
- W4385819626 hasConceptScore W4385819626C108583219 @default.