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008			210923s2021 sz | s |||| 0|eng d
020			_a9783030761677
024	7		_a10.1007/978-3-030-76167-7 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQ325.5 _b2021 EB
245	1	0	_aConcepts and Real-Time Applications of Deep Learning _cedited by Smriti Srivastava, Manju Khari, Ruben Gonzalez Crespo, Gopal Chaudhary, Parul Arora.
250			_aFirst edition 2021
264		1	_aCham _bSpringer International Pulishing _c2021
300			_a1 recurso en línea (X, 209 páginas) _b86 ilustraciones, 74 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aEAI/Springer Innovations in Communication and Computing _x2522-8609
490	0		_aIntelligent Technologies and Robotics (SpringerNature-42732)
490	0		_aIntelligent Technologies and Robotics (R0) (SpringerNature-43728)
505	0		_aIntroduction -- AI Techniques based on Modern Deep Learning architectures -- Application of Deep learning in Optimization and Regression -- Deep learning in Pattern recognition -- Application of Deep Learning in Healthcare systems for diagnosing disease -- Application of Deep Learning for Security and threats -- Deep Learning Framework and Tools -- Advancements in Deep Learning -- Multidisciplinary Applications of Machine/Deep Learning -- Conclusion.
520	3		_aThis book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a concentration on advances of deep learning architectures. The book discusses various artificial intelligence (AI) techniques based on deep learning architecture with applications in natural language processing, semantic knowledge, forecasting and many more. The authors shed light on various applications that can benefit from the use of deep learning in pattern recognition, person re-identification in surveillance videos, action recognition in videos, image and video captioning. The book also highlights how deep learning concepts can be interwoven with more modern concepts to yield applications in multidisciplinary fields. Presents a comprehensive look at deep learning and its multidisciplinary applications, concentrating on advances of deep learning architectures; Includes a survey of deep learning problems and solutions, identifying the main open issues, innovations and latest technologies; Shows industrial deep learning in practice with examples/cases, efforts, challenges, and strategic approaches.
988			_aSpringer_Robotics_2021
650		7	_2embne _9166090 _aAprendizaje automático
700	1		_aSrivastava, Smriti _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _9681782
700	1		_aKhari, Manju _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _9681783
700	1		_aGonzález Crespo, Rubén A. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _9681784
700	1		_aChaudhary, Gopal _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _9681785
700			_aArora, Parul _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _9681786
776	0	8	_iPrinted edition: _z9783030761660
776	0	8	_iPrinted edition: _z9783030761684
776	0	8	_iPrinted edition: _z9783030761691
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-76167-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE