000			03663cam a22006015i 4500
001			21675720
003			OSt
005			20220826172551.0
006			m |o d |
007			cr |||||||||||
008			190314s2020 si |||| o |||| 0|eng
010			_a 2019743646
020			_a9789811367946 (pbk.)
024	7		_a10.1007/978-981-13-6794-6 _2doi
035			_a(DE-He213)978-981-13-6794-6
040			_aDLC _beng _epn _erda _cJKRC
082	0	4	_a006.3 _223 _bWAN
100	1		_aWani, M. Arif. _eAuthor. _92661
245	1	0	_aAdvances in Deep Learning / _cby M. Arif Wani [et. al..]
250			_a1st
260			_aSingapore : _bImprint: Springer, _c2020.
300			_aXIV, 149 p. ; _c24cm. _b87 illustrations, 53 illustrations in color
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
365			_b149.99 _cEuros
490	1		_aStudies in Big Data, _x2197-6503 ; _v57
505	0		_aPreface -- Introduction to Deep Learning -- Basic Deep Learning Models -- Training Basic Deep Learning Models -- Optimising Deep Learning Models -- Application of Deep Learning in Classification -- Application of Deep Learning in Segmentation -- Application of Deep Learning in Face Recognition -- Application of Deep Learning in Fingerprint Recognition -- Author's Index.
520			_aThis book introduces readers to both basic and advanced concepts in deep network models. It covers state-of-the-art deep architectures that many researchers are currently using to overcome the limitations of the traditional artificial neural networks. Various deep architecture models and their components are discussed in detail, and subsequently illustrated by algorithms and selected applications. In addition, the book explains in detail the transfer learning approach for faster training of deep models; the approach is also demonstrated on large volumes of fingerprint and face image datasets. In closing, it discusses the unique set of problems and challenges associated with these models.
588			_aDescription based on publisher-supplied MARC data.
650		0	_aArtificial intelligence. _92662
650		0	_aBig data. _92663
650		0	_aComputational intelligence. _92664
650		0	_aNeural networks (Computer science). _92665
650		0	_aOptical data processing. _92666
650	1	4	_aComputational Intelligence. _0https://scigraph.springernature.com/ontologies/product-market-codes/T11014 _92667
650	2	4	_aArtificial Intelligence. _0https://scigraph.springernature.com/ontologies/product-market-codes/I21000 _92668
650	2	4	_aBig Data. _0https://scigraph.springernature.com/ontologies/product-market-codes/I29120 _92669
650	2	4	_aComputer Imaging, Vision, Pattern Recognition and Graphics. _0https://scigraph.springernature.com/ontologies/product-market-codes/I22005 _92670
650	2	4	_aMathematical Models of Cognitive Processes and Neural Networks. _0https://scigraph.springernature.com/ontologies/product-market-codes/M13100 _92671
653			_aLinear models (Statistics) _aProbabilities _aStatistics
700	1		_aAfzal, Saduf. _eauthor. _92672
700	1		_aBhat, Farooq Ahmad. _eauthor. _92673
700	1		_aKhan, Asif Iqbal. _eauthor. _92674
776	0	8	_iPrint version: _tAdvances in deep learning. _z9789811367939 _w(DLC) 2019932671
776	0	8	_iPrinted edition: _z9789811367939
776	0	8	_iPrinted edition: _z9789811367953
776	0	8	_iPrinted edition: _z9789811367960
830		0	_aStudies in Big Data, _x2197-6503 ; _v57 _92675
906			_a0 _bibc _corigres _du _encip _f20 _gy-gencatlg
942			_2ddc _c1 _e23 _n0
999			_c400284 _d400284