Matches in SemOpenAlex for { <https://semopenalex.org/work/W3183648003> ?p ?o ?g. }
Showing items 1 to 77 of
77
with 100 items per page.
- W3183648003 endingPage "6824" @default.
- W3183648003 startingPage "6824" @default.
- W3183648003 abstract "Electromyogram (EMG) signals cannot be forged and have the advantage of being able to change the registered data as they are characterized by the waveform, which varies depending on the gesture. In this paper, a two-step biometrics method was proposed using EMG signals based on a convolutional neural network–long short-term memory (CNN-LSTM) network. After preprocessing of the EMG signals, the time domain features and LSTM network were used to examine whether the gesture matched, and single biometrics was performed if the gesture matched. In single biometrics, EMG signals were converted into a two-dimensional spectrogram, and training and classification were performed through the CNN-LSTM network. Data fusion of the gesture recognition and single biometrics was performed in the form of an AND. The experiment used Ninapro EMG signal data as the proposed two-step biometrics method, and the results showed 83.91% gesture recognition performance and 99.17% single biometrics performance. In addition, the false acceptance rate (FAR) was observed to have been reduced by 64.7% through data fusion." @default.
- W3183648003 created "2021-08-02" @default.
- W3183648003 creator A5060421734 @default.
- W3183648003 creator A5066435456 @default.
- W3183648003 creator A5072004665 @default.
- W3183648003 date "2021-07-25" @default.
- W3183648003 modified "2023-10-07" @default.
- W3183648003 title "Two-Step Biometrics Using Electromyogram Signal Based on Convolutional Neural Network-Long Short-Term Memory Networks" @default.
- W3183648003 cites W1984150290 @default.
- W3183648003 cites W2089960242 @default.
- W3183648003 cites W2130948728 @default.
- W3183648003 cites W2169931829 @default.
- W3183648003 cites W2878521835 @default.
- W3183648003 cites W2920903378 @default.
- W3183648003 cites W2921988675 @default.
- W3183648003 cites W2922138935 @default.
- W3183648003 cites W2999874993 @default.
- W3183648003 cites W3001314219 @default.
- W3183648003 cites W3003010063 @default.
- W3183648003 cites W3010923682 @default.
- W3183648003 cites W3037235457 @default.
- W3183648003 doi "https://doi.org/10.3390/app11156824" @default.
- W3183648003 hasPublicationYear "2021" @default.
- W3183648003 type Work @default.
- W3183648003 sameAs 3183648003 @default.
- W3183648003 citedByCount "9" @default.
- W3183648003 countsByYear W31836480032022 @default.
- W3183648003 countsByYear W31836480032023 @default.
- W3183648003 crossrefType "journal-article" @default.
- W3183648003 hasAuthorship W3183648003A5060421734 @default.
- W3183648003 hasAuthorship W3183648003A5066435456 @default.
- W3183648003 hasAuthorship W3183648003A5072004665 @default.
- W3183648003 hasBestOaLocation W31836480032 @default.
- W3183648003 hasConcept C153180895 @default.
- W3183648003 hasConcept C154945302 @default.
- W3183648003 hasConcept C184297639 @default.
- W3183648003 hasConcept C199360897 @default.
- W3183648003 hasConcept C207347870 @default.
- W3183648003 hasConcept C2779843651 @default.
- W3183648003 hasConcept C28490314 @default.
- W3183648003 hasConcept C34736171 @default.
- W3183648003 hasConcept C41008148 @default.
- W3183648003 hasConcept C45273575 @default.
- W3183648003 hasConcept C81363708 @default.
- W3183648003 hasConceptScore W3183648003C153180895 @default.
- W3183648003 hasConceptScore W3183648003C154945302 @default.
- W3183648003 hasConceptScore W3183648003C184297639 @default.
- W3183648003 hasConceptScore W3183648003C199360897 @default.
- W3183648003 hasConceptScore W3183648003C207347870 @default.
- W3183648003 hasConceptScore W3183648003C2779843651 @default.
- W3183648003 hasConceptScore W3183648003C28490314 @default.
- W3183648003 hasConceptScore W3183648003C34736171 @default.
- W3183648003 hasConceptScore W3183648003C41008148 @default.
- W3183648003 hasConceptScore W3183648003C45273575 @default.
- W3183648003 hasConceptScore W3183648003C81363708 @default.
- W3183648003 hasIssue "15" @default.
- W3183648003 hasLocation W31836480031 @default.
- W3183648003 hasLocation W31836480032 @default.
- W3183648003 hasOpenAccess W3183648003 @default.
- W3183648003 hasPrimaryLocation W31836480031 @default.
- W3183648003 hasRelatedWork W1976719989 @default.
- W3183648003 hasRelatedWork W2011227383 @default.
- W3183648003 hasRelatedWork W2016904525 @default.
- W3183648003 hasRelatedWork W2065606036 @default.
- W3183648003 hasRelatedWork W2088854863 @default.
- W3183648003 hasRelatedWork W2530685530 @default.
- W3183648003 hasRelatedWork W2942893872 @default.
- W3183648003 hasRelatedWork W3179495260 @default.
- W3183648003 hasRelatedWork W4375868962 @default.
- W3183648003 hasRelatedWork W325696142 @default.
- W3183648003 hasVolume "11" @default.
- W3183648003 isParatext "false" @default.
- W3183648003 isRetracted "false" @default.
- W3183648003 magId "3183648003" @default.
- W3183648003 workType "article" @default.