000 | 04745nam a22005895i 4500 | ||
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001 | 978-3-030-74697-1 | ||
003 | DE-He213 | ||
005 | 20240423125453.0 | ||
007 | cr nn 008mamaa | ||
008 | 210816s2021 sz | s |||| 0|eng d | ||
020 |
_a9783030746971 _9978-3-030-74697-1 |
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024 | 7 |
_a10.1007/978-3-030-74697-1 _2doi |
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050 | 4 | _aTA1634 | |
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_aUYQV _2bicssc |
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_aCOM016000 _2bisacsh |
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_aUYQV _2thema |
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_a006.37 _223 |
245 | 1 | 0 |
_aDeep Learning-Based Face Analytics _h[electronic resource] / _cedited by Nalini K Ratha, Vishal M. Patel, Rama Chellappa. |
250 | _a1st ed. 2021. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2021. |
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300 |
_aVI, 407 p. 182 illus., 169 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aAdvances in Computer Vision and Pattern Recognition, _x2191-6594 |
|
505 | 0 | _a1. Deep CNN Face Recognition: Looking at the Past and the Future -- 2. Face Segmentation, Face Swapping, and Their Effect on Face Recognition -- 3. Disentangled Representation Learning and its Application to Face Analytics -- 4. Learning 3D Face Morphable Model from In-the-wild Images -- 5. Deblurring Face Images using Deep Networks -- 6. Blind-Superresolution of Faces for Surveillance -- 7. Hashing a Face. | |
520 | _aThis book provides an overview of different deep learning-based methods for face recognition and related problems. Specifically, the authors present methods based on autoencoders, restricted Boltzmann machines, and deep convolutional neural networks for face detection, localization, tracking, recognition, etc. The authors also discuss merits and drawbacks of available approaches and identifies promising avenues of research in this rapidly evolving field. Even though there have been a number of different approaches proposed in the literature for face recognition based on deep learning methods, there is not a single book available in the literature that gives a complete overview of these methods. The proposed book captures the state of the art in face recognition using various deep learning methods, and it covers a variety of different topics related to face recognition. The prerequisites for optimal use are the basic knowledge of pattern recognition, machine learning, probability theory, and linear algebra. This book is aimed at graduate students studying electrical engineering and/or computer science. Biometrics is a course that is widely offered at both undergraduate and graduate levels at many institutions around the world: This book can be used as a textbook for teaching topics related to face recognition. In addition, the work is beneficial to practitioners in industry who are working on biometrics-related problems. Nalini K. Ratha is Empire Innovation professor in the Department of Computer Science and Engineering at University at Buffalo (New York). He is co-author and co-editor, respectively, of the Springer books, Guide to Biometrics and Advances in Biometrics. Vishal M. Patel is Assistant Professor in the Department of Electrical and Computer Engineering at Johns Hopkins University (JHU). Rama Chellappa is Bloomberg Distinguished Professor in the Departments ofElectrical and Computer Engineering and Biomedical Engineering at JHU. He is co-author and co-editor, respectively, of the Springer books, Unconstrained Face Recognition and Handbook of Remote Biometrics. | ||
650 | 0 | _aComputer vision. | |
650 | 0 | _aBiometric identification. | |
650 | 0 | _aMachine learning. | |
650 | 0 | _aNeural networks (Computer science) . | |
650 | 1 | 4 | _aComputer Vision. |
650 | 2 | 4 | _aBiometrics. |
650 | 2 | 4 | _aMachine Learning. |
650 | 2 | 4 | _aMathematical Models of Cognitive Processes and Neural Networks. |
700 | 1 |
_aRatha, Nalini K. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aPatel, Vishal M. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aChellappa, Rama. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783030746964 |
776 | 0 | 8 |
_iPrinted edition: _z9783030746988 |
776 | 0 | 8 |
_iPrinted edition: _z9783030746995 |
830 | 0 |
_aAdvances in Computer Vision and Pattern Recognition, _x2191-6594 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-74697-1 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cSPRINGER | ||
999 |
_c178281 _d178281 |