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008			220402s2022 sz | s |||| 0|eng d
020			_a9783030913908
024	7		_a10.1007/978-3-030-91390-8 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQ325.5 _b2022 EB
245	0	0	_aGenerative Adversarial Learning: Architectures and Applications _cedited by Roozbeh Razavi-Far, Ariel Ruiz-Garcia, Vasile Palade, Juergen Schmidhuber
250			_aFirst edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XIV, 355 páginas) _b145 ilustraciones, 132 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aIntelligent Systems Reference Library _x1868-4408 _v217
505	0		_aAn Introduction to Generative Adversarial Learning: Architectures and Applications -- Generative Adversarial Networks: A Survey on Training, Variants, and Applications -- Fair Data Generation and Machine Learning through Generative Adversarial Networks.
520			_aThis book provides a collection of recent research works addressing theoretical issues on improving the learning process and the generalization of GANs as well as state-of-the-art applications of GANs to various domains of real life. Adversarial learning fascinates the attention of machine learning communities across the world in recent years. Generative adversarial networks (GANs), as the main method of adversarial learning, achieve great success and popularity by exploiting a minimax learning concept, in which two networks compete with each other during the learning process. Their key capability is to generate new data and replicate available data distributions, which are needed in many practical applications, particularly in computer vision and signal processing. The book is intended for academics, practitioners, and research students in artificial intelligence looking to stay up to date with the latest advancements on GANs' theoretical developments and their applications.
988			_aSpringer_Robotics_2022
650		7	_2embne _9166090 _aAprendizaje automático
650		7	_2embne _9150608 _aProceso de señales
650		7	_2embne _9678664 _aRedes neuronales artificiales
700	1		_aRazavi-Far, Roozbeh _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aRuiz-Garcia, Ariel _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700			_aPalade, Vasile. _eeditor literario _0(orcid)0000-0002-6768-8394 _1https://orcid.org/0000-0002-6768-8394 _4edt _4http://id.loc.gov/vocabulary/relators/edt _998066
700	1		_aSchmidhuber, Juergen _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9783030913892
776	0	8	_iPrinted edition: _z9783030913915
776	0	8	_iPrinted edition: _z9783030913922
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-91390-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b04/2022 _dz _eIG _zSI