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020			_a9783030317607
024	7		_a10.1007/978-3-030-31760-7 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
041	0		_aeng
050		4	_aQ325.5 _b2020 EB
245	0	0	_aDeep Learning: Algorithms and Applications _cedited by Witold Pedrycz, Shyi-Ming Chen
250			_aFirst edition
264		1	_aCham _bSpringer International Publishing : _bImprint Springer _c2020
300			_a1 recurso en línea (XII, 360 páginas) _b171 ilustraciones, 139 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aStudies in Computational Intelligence _x1860-949X _v865
490	0		_aIntelligent Technologies and Robotics (Springer-42732)
505	0		_aPreface -- Chapter 1. Activation Functions -- Chapter 2. Adversarial Examples in Deep Neural Networks: An Overview -- Chapter 3. Representation Learning in Power Time Series Forecasting, etc.
520	3		_aThis book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent alignment with the essential characteristics of the nature of learning encountered in the practical problems being tackled. Intended for readers interested in acquiring practical knowledge of analysis, design, and deployment of deep learning solutions to real-world problems, it covers a wide range of the paradigm's algorithms and their applications in diverse areas including imaging, seismic tomography, smart grids, surveillance and security, and health care, among others. Featuring systematic and comprehensive discussions on the development processes, their evaluation, and relevance, the book offers insights into fundamental design strategies for algorithms of deep learning.
988			_aPrimersemestre_2020_Robotics
650		7	_2embne _aAprendizaje automático _9166090
700	1		_aPedrycz, Witold _d1953- _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt _967495
700	1		_aChen, Shyi-Ming _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt _998849
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783030317591
776	0	8	_iPrinted edition: _z9783030317614
776	0	8	_iPrinted edition: _z9783030317621
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-31760-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b03/2020 _dz _eb _zSI