Advanced Biometrics with Deep Learning
Biometrics, such as fingerprint, iris, face, hand print, hand vein, speech and gait recognition, etc., as a means of identity management have become commonplace nowadays for various applications. Biometric systems follow a typical pipeline, that is composed of separate preprocessing, feature extract...
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| Formato: | Online |
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| Idioma: | inglês |
| Publicado em: |
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Acesso em linha: | ONIX_20210501_9783039366989_615 |
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| _version_ | 1869521639931117568 |
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| collection | Directory of Open Access Books |
| description | Biometrics, such as fingerprint, iris, face, hand print, hand vein, speech and gait recognition, etc., as a means of identity management have become commonplace nowadays for various applications. Biometric systems follow a typical pipeline, that is composed of separate preprocessing, feature extraction and classification. Deep learning as a data-driven representation learning approach has been shown to be a promising alternative to conventional data-agnostic and handcrafted pre-processing and feature extraction for biometric systems. Furthermore, deep learning offers an end-to-end learning paradigm to unify preprocessing, feature extraction, and recognition, based solely on biometric data. This Special Issue has collected 12 high-quality, state-of-the-art research papers that deal with challenging issues in advanced biometric systems based on deep learning. The 12 papers can be divided into 4 categories according to biometric modality; namely, face biometrics, medical electronic signals (EEG and ECG), voice print, and others. |
| format | Online |
| id | doab-20.500.12854ir-68869 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-688692024-04-11T15:10:17Z Advanced Biometrics with Deep Learning Jin, Andrew Leng, Lu thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Biometrics, such as fingerprint, iris, face, hand print, hand vein, speech and gait recognition, etc., as a means of identity management have become commonplace nowadays for various applications. Biometric systems follow a typical pipeline, that is composed of separate preprocessing, feature extraction and classification. Deep learning as a data-driven representation learning approach has been shown to be a promising alternative to conventional data-agnostic and handcrafted pre-processing and feature extraction for biometric systems. Furthermore, deep learning offers an end-to-end learning paradigm to unify preprocessing, feature extraction, and recognition, based solely on biometric data. This Special Issue has collected 12 high-quality, state-of-the-art research papers that deal with challenging issues in advanced biometric systems based on deep learning. The 12 papers can be divided into 4 categories according to biometric modality; namely, face biometrics, medical electronic signals (EEG and ECG), voice print, and others. 2021-05-01T15:31:43Z 2021-05-01T15:31:43Z 2020 book ONIX_20210501_9783039366989_615 9783039366989 9783039366996 https://directory.doabooks.org/handle/20.500.12854/68869 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/2636 https://mdpi.com/books/pdfview/book/2636 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03936-699-6 10.3390/books978-3-03936-699-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039366989 9783039366996 210 Basel, Switzerland open access |
| spellingShingle | thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Advanced Biometrics with Deep Learning |
| title | Advanced Biometrics with Deep Learning |
| title_full | Advanced Biometrics with Deep Learning |
| title_fullStr | Advanced Biometrics with Deep Learning |
| title_full_unstemmed | Advanced Biometrics with Deep Learning |
| title_short | Advanced Biometrics with Deep Learning |
| title_sort | advanced biometrics with deep learning |
| topic | thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | ONIX_20210501_9783039366989_615 |