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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Format: | Electronic Book Chapter |
Language: | English |
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Basel, Switzerland
MDPI - Multidisciplinary Digital Publishing Institute
2020
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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042 | |a dc | ||
072 | 7 | |a TBX |2 bicssc | |
100 | 1 | |a Jin, Andrew |4 edt | |
700 | 1 | |a Leng, Lu |4 edt | |
700 | 1 | |a Jin, Andrew |4 oth | |
700 | 1 | |a Leng, Lu |4 oth | |
245 | 1 | 0 | |a Advanced Biometrics with Deep Learning |
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506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a 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. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a History of engineering & technology |2 bicssc | |
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/2636 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/68869 |7 0 |z DOAB: description of the publication |