Applications of Recurrent Neural Network for Biometric Authentication & Anomaly Detection
Recurrent Neural Networks are powerful machine learning frameworks that allow for data to be saved and referenced in a temporal sequence. This opens many new possibilities in fields such as handwriting analysis and speech recognition. This paper seeks to explore current research being conducted on R...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/12/7/272 |
| _version_ | 1797526849724612608 |
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| author | Joseph M. Ackerson Rushit Dave Naeem Seliya |
| author_facet | Joseph M. Ackerson Rushit Dave Naeem Seliya |
| author_sort | Joseph M. Ackerson |
| collection | DOAJ |
| description | Recurrent Neural Networks are powerful machine learning frameworks that allow for data to be saved and referenced in a temporal sequence. This opens many new possibilities in fields such as handwriting analysis and speech recognition. This paper seeks to explore current research being conducted on RNNs in four very important areas, being biometric authentication, expression recognition, anomaly detection, and applications to aircraft. This paper reviews the methodologies, purpose, results, and the benefits and drawbacks of each proposed method below. These various methodologies all focus on how they can leverage distinct RNN architectures such as the popular Long Short-Term Memory (LSTM) RNN or a Deep-Residual RNN. This paper also examines which frameworks work best in certain situations, and the advantages and disadvantages of each proposed model. |
| first_indexed | 2024-03-10T09:36:10Z |
| format | Article |
| id | doaj.art-426bae5a9d564f2a84ccd1537236453a |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-10T09:36:10Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-426bae5a9d564f2a84ccd1537236453a2023-11-22T04:03:48ZengMDPI AGInformation2078-24892021-07-0112727210.3390/info12070272Applications of Recurrent Neural Network for Biometric Authentication & Anomaly DetectionJoseph M. Ackerson0Rushit Dave1Naeem Seliya2Department of Computer Science, University of Wisconsin Eau-Claire, Eau Claire, WI 54701, USADepartment of Computer Science, University of Wisconsin Eau-Claire, Eau Claire, WI 54701, USADepartment of Computer Science, University of Wisconsin Eau-Claire, Eau Claire, WI 54701, USARecurrent Neural Networks are powerful machine learning frameworks that allow for data to be saved and referenced in a temporal sequence. This opens many new possibilities in fields such as handwriting analysis and speech recognition. This paper seeks to explore current research being conducted on RNNs in four very important areas, being biometric authentication, expression recognition, anomaly detection, and applications to aircraft. This paper reviews the methodologies, purpose, results, and the benefits and drawbacks of each proposed method below. These various methodologies all focus on how they can leverage distinct RNN architectures such as the popular Long Short-Term Memory (LSTM) RNN or a Deep-Residual RNN. This paper also examines which frameworks work best in certain situations, and the advantages and disadvantages of each proposed model.https://www.mdpi.com/2078-2489/12/7/272recurrent neural networkbiometric authenticationexpression recognitionanomaly detectionsmartphone authenticationmouse-based authentication |
| spellingShingle | Joseph M. Ackerson Rushit Dave Naeem Seliya Applications of Recurrent Neural Network for Biometric Authentication & Anomaly Detection Information recurrent neural network biometric authentication expression recognition anomaly detection smartphone authentication mouse-based authentication |
| title | Applications of Recurrent Neural Network for Biometric Authentication & Anomaly Detection |
| title_full | Applications of Recurrent Neural Network for Biometric Authentication & Anomaly Detection |
| title_fullStr | Applications of Recurrent Neural Network for Biometric Authentication & Anomaly Detection |
| title_full_unstemmed | Applications of Recurrent Neural Network for Biometric Authentication & Anomaly Detection |
| title_short | Applications of Recurrent Neural Network for Biometric Authentication & Anomaly Detection |
| title_sort | applications of recurrent neural network for biometric authentication anomaly detection |
| topic | recurrent neural network biometric authentication expression recognition anomaly detection smartphone authentication mouse-based authentication |
| url | https://www.mdpi.com/2078-2489/12/7/272 |
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