000			03867nam a2200541Ii 4500
001			9781351265003
008			180727s2018 fluab ob 001 0 eng d
020			_a9781351265003 _q(e-book : PDF)
035			_a(OCoLC)1019715986
040			_aFlBoTFG _cFlBoTFG _erda
050		4	_aTK7882.B56
060	1	0	_aW 786
072		7	_aCOM _x021030 _2bisacsh
072		7	_aCOM _x037000 _2bisacsh
072		7	_aTEC _x015000 _2bisacsh
072		7	_aUN _2bicscc
082	0	4	_a570.1/5195 _223
245	0	0	_aDeep learning in biometrics / _cedited by Mayank Vatsa, Richa Singh and Angshul Majumdar.
250			_aFirst edition.
264		1	_aBoca Raton, FL : _bCRC Press, an imprint of Taylor and Francis, _c2018.
300			_a1 online resource (328 pages) : _b153 illustrations
336			_atext _2rdacontent
337			_acomputer _2rdamedia
338			_aonline resource _2rdacarrier
505	0	0	_tchapter 1 Deep Learning: Fundamentals and Beyond / _rShruti Nagpal -- _tchapter 2 Unconstrained Face Identification and Verification Using Deep Convolutional Features / _rJun-Cheng Chen * -- _tchapter 3 Deep Siamese Convolutional Neural Networks for Identical Twins and Look-Alike Identification / _rXiaoxia Sun -- _tchapter 4 Tackling the Optimization and Precision Weakness of Deep Cascaded Regression for Facial Key-Point Localization / _rYuhang Wu -- _tchapter 5 Learning Deep Metrics for Person Reidentification / _rHailin Shi -- _tchapter 6 Deep Face-Representation Learning for Kinship Verification / _rNaman Kohli -- _tchapter 7 What's Hiding in My Deep Features? / _rEthan M. Rudd -- _tchapter 8 Stacked Correlation Filters / _rJonathon M. Smereka -- _tchapter 9 Learning Representations for Unconstrained Fingerprint Recognition / _rAakarsh Malhotra -- _tchapter 10 Person Identification Using Handwriting Dynamics and Convolutional Neural Networks / _rGustavo H. Rosa -- _tchapter 11 Counteracting Presentation Attacks in Face, Fingerprint, and Iris Recognition / _rAllan Pinto -- _tchapter 12 Fingervein Presentation Attack Detection Using Transferable Features from Deep Convolution Neural Networks / _rRaghavendra Ramachandra.
520	3		_aDeep Learning is now synonymous with applied machine learning. Many technology giants (e.g. Google, Microsoft, Apple, IBM) as well as start-ups are focusing on deep learning-based techniques for data analytics and artificial intelligence. This technology applies quite strongly to biometrics. This book covers topics in deep learning, namely convolutional neural networks, deep belief network and stacked autoencoders. The focus is also on the application of these techniques to various biometric modalities: face, iris, palmprint, and fingerprints, while examining the future trends in deep learning and biometric research.
650	1	2	_aBiometric Identification. _911407
650	2	2	_aMachine Learning. _91831
650		0	_aBiometric Identification. _911407
650		0	_aMachine Learning. _91831
650		7	_aSCIENCE _xLife Sciences _vGeneral. _2bisacsh _918324
650		7	_aTECHNOLOGY & ENGINEERING _xElectronics _vGeneral. _2bisacsh _918325
650		7	_aCOMPUTERS / Machine Theory. _2bisacsh _918326
650		7	_aTECHNOLOGY & ENGINEERING / Imaging Systems. _2bisacsh _99703
650		0	_aDeep Metric Learning. _918327
650		0	_aFace Recognition. _918328
650		0	_aMetric Learning. _918329
650		0	_aMultispectral Iris Recognition. _918330
650		0	_aOcular Recognition. _918331
650		0	_a3D Processing With Deep Learning. _918332
700	1		_aSingh, Richa, _d1980- _eeditor. _918333
700	1		_aVatsa, Mayank, _eeditor. _918334
700	1		_aMajumdar, Angshul, _eeditor. _918335
710	2		_aTaylor and Francis. _910719
776	0	8	_iPrint version: _z9781138578234 _w(DLC) 2017037884
856	4	0	_uhttps://www.taylorfrancis.com/books/9781351265003 _zClick here to view.
942			_cEBK
999			_c71767 _d71767