Articoli correlati a Computational Methods for Deep Learning: Theoretic,...

Computational Methods for Deep Learning: Theoretic, Practice and Applications - Brossura

 
9783030610838: Computational Methods for Deep Learning: Theoretic, Practice and Applications

Sinossi

<p>Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from graphical theory, mathematical models, and algorithmic implementation, as well as covers datasets preparation, programming, results analysis and evaluations.</p><p>Beginning with a grounding about artificial neural networks with neurons and the activation functions, the work then explains the mechanism of deep learning using advanced mathematics. In particular, it emphasizes how to use TensorFlow and the latest MATLAB deep-learning toolboxes for implementing deep learning algorithms.</p><p>As a prerequisite, readers should have a solid understanding especially of mathematical analysis, linear algebra, numerical analysis, optimizations, differential geometry, manifold, and information theory, as well as basic algebra, functional analysis, and graphical models. This computational knowledge will assist in comprehending the subject matter not only of this text/reference, but also in relevant deep learning journal articles and conference papers.</p><p>This textbook/guide is aimed at Computer Science research students and engineers, as well as scientists interested in deep learning for theoretic research and analysis. More generally, this book is also helpful for those researchers who are interested in machine intelligence, pattern analysis, natural language processing, and machine vision.</p><p><b>Dr. Wei Qi Yan</b>&nbsp;is an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title,&nbsp;<i>Visual Cryptography for Image Processing and Security</i>.&nbsp; &nbsp; &nbsp; &nbsp;</p><div><br></div><p></p>

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull?autore

<p><b>Dr. Wei Qi Yan</b> received a doctorate degree of computer engineering from the Chinese Academy of Sciences, Beijing, China in 2001, he moved to the School of Computing (SoC), National University of Singapore, and worked as a Research Fellow, later as a regular faculty member from 2003 to 2005. In 2005, he joined the Columbia University in New York City, USA, as a Research Scholar. He moved to the University of California, Irvine USA in 2006. He joined the Queen’s University Belfast (Russell Group UK), as a Lecturer in 2007 and moved to the Auckland University of Technology (AUT), New Zealand in 2011; he is the Director of Computer and Cyber Security (CCS) Research Group since 2011 and the Deputy Director of CeRV (Robotics & Vision) research centre since 2015, the Director of CeRV from 2019.</p><p>Dr. Yan has contributed to 13 granted research proposals. He has co-authored 13 research books as well as over 230 publications (J: 80+) with more than 2,900 Google citations, one of his research papers has been cited over 700 times. His publications have been accepted or appeared in the ACM and IEEE journals and conferences. Dr. Yan’s research distinctions at AUT include deep learning, intelligent surveillance, currency security, visual cryptography, digital event computing, intelligent navigations, etc. Dr. Yan is a regular reviewer of Ph.D. theses of AUT, the Massey University, the University of Canterbury, the University of Auckland (UoA), New Zealand, and the Nanyang Technological University (NTU), Singapore.</p><p>Dr. Yan’s services have included being a TPC member of all the top ACM and IEEE conferences in his research area, Track Chair of IEEE VCIP 2020 and IEEE ICME 2020, Publication Chair of IAPR ACPR 2019, Program Chair of IEEE AVSS 2018, General Chair of ISGV2021 and IWDW 2013, and Program Chair of WSVS 2015 and IWDCF 2015/2016/2017. Dr. Yan has delivered over 100 talks around the world, and his visit to the Chinese Academy of Sciences China was sponsored by the Royal Society of New Zealand (RSNZ), Ministry of Science and Technology (MOST) China in 2013. He is an Adjunct Professor of the Chinese Academy of Sciences, China, with Ph.D. supervision. Dr. Yan was a Visiting Professor of the University of Auckland (UoA), the Massey University,&nbsp;and the National University of Singapore (NUS).</p><p>Dr. Yan is serving as the Editor-in-Chief (EiC) of the International Journal Digital Crime Forensics (IJDCF) from 2014 to 2019, now an Editor-inChief Emeritus;&nbsp;a Guest Editor of the Springer Transactions on Data Hiding and Multimedia Security (DHMS), a book reviewer of John Wiley and Sons, IGI global, and a proposal reviewer of Ministry of Business, Innovation, and Employment (MBIE) of New Zealand. He is also a member of the ACM, the Chair of ACM New Zealand chapter in Multimedia, a senior member of the IEEE, TC members of the IEEE, and a Fellow of the Higher Education Academy (FHEA), UK.</p><p><b>Dr. Wei Qi Yan</b> is an Associate Professor with the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer books: <i>Visual Cryptography for Image Processing and Security;&nbsp; Introduction to Intelligent Surveillance.</i></p><br>

Dalla quarta di copertina

<p>Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from graphical theory, mathematical models, and algorithmic implementation, as well as covers datasets preparation, programming, results analysis and evaluations.</p><p>Beginning with a grounding about artificial neural networks with neurons and the activation functions, the work then explains the mechanism of deep learning using advanced mathematics. In particular, it emphasizes how to use TensorFlow and the latest MATLAB deep-learning toolboxes for implementing deep learning algorithms.</p><p>As a prerequisite, readers should have a solid understanding especially of mathematical analysis, linear algebra, numerical analysis, optimizations, differential geometry, manifold, and information theory, as well as basic algebra, functional analysis, and graphical models. This computational knowledge will assist in comprehending the subject matter not only of this text/reference, but also in relevant deep learning journal articles and conference papers.</p><p>This textbook/guide is aimed at Computer Science research students and engineers, as well as scientists interested in deep learning for theoretic research and analysis. More generally, this book is also helpful for those researchers who are interested in machine intelligence, pattern analysis, natural language processing, and machine vision.</p><p><b>Dr. Wei Qi Yan</b> is an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title, <i>Visual Cryptography for Image Processing and Security</i>.&nbsp; &nbsp; &nbsp; &nbsp;</p><br><p></p>

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

GRATIS per la spedizione da U.S.A. a Italia

Destinazione, tempi e costi

Altre edizioni note dello stesso titolo

9783030610807: Computational Methods for Deep Learning: Theoretic, Practice and Applications

Edizione in evidenza

ISBN 10:  3030610802 ISBN 13:  9783030610807
Casa editrice: Springer-Nature New York Inc, 2020
Rilegato

Risultati della ricerca per Computational Methods for Deep Learning: Theoretic,...

Foto dell'editore

YAN
Editore: Springer, 2021
ISBN 10: 3030610837 ISBN 13: 9783030610838
Nuovo Brossura

Da: Basi6 International, Irving, TX, U.S.A.

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Codice articolo ABEJUNE24-325311

Contatta il venditore

Compra nuovo

EUR 58,74
Convertire valuta
Spese di spedizione: GRATIS
Da: U.S.A. a: Italia
Destinazione, tempi e costi

Quantità: 2 disponibili

Aggiungi al carrello

Foto dell'editore

Wei Qi Yan
Editore: Springer, 2021
ISBN 10: 3030610837 ISBN 13: 9783030610838
Nuovo Brossura

Da: Books Puddle, New York, NY, U.S.A.

Valutazione del venditore 4 su 5 stelle 4 stelle, Maggiori informazioni sulle valutazioni dei venditori

Condizione: New. Codice articolo 26390225112

Contatta il venditore

Compra nuovo

EUR 56,72
Convertire valuta
Spese di spedizione: EUR 7,74
Da: U.S.A. a: Italia
Destinazione, tempi e costi

Quantità: 1 disponibili

Aggiungi al carrello

Immagini fornite dal venditore

Yan, Wei Qi
ISBN 10: 3030610837 ISBN 13: 9783030610838
Nuovo Brossura
Print on Demand

Da: moluna, Greven, Germania

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine int. Codice articolo 525691931

Contatta il venditore

Compra nuovo

EUR 55,78
Convertire valuta
Spese di spedizione: EUR 9,70
Da: Germania a: Italia
Destinazione, tempi e costi

Quantità: Più di 20 disponibili

Aggiungi al carrello

Foto dell'editore

Qi Yan Wei
Editore: Springer, 2021
ISBN 10: 3030610837 ISBN 13: 9783030610838
Nuovo Brossura

Da: Biblios, Frankfurt am main, HESSE, Germania

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Condizione: New. Codice articolo 18390225106

Contatta il venditore

Compra nuovo

EUR 59,76
Convertire valuta
Spese di spedizione: EUR 7,95
Da: Germania a: Italia
Destinazione, tempi e costi

Quantità: 1 disponibili

Aggiungi al carrello

Foto dell'editore

Qi Yan Wei
Editore: Springer, 2021
ISBN 10: 3030610837 ISBN 13: 9783030610838
Nuovo Brossura

Da: Majestic Books, Hounslow, Regno Unito

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Condizione: New. Codice articolo 389407495

Contatta il venditore

Compra nuovo

EUR 57,62
Convertire valuta
Spese di spedizione: EUR 10,20
Da: Regno Unito a: Italia
Destinazione, tempi e costi

Quantità: 1 disponibili

Aggiungi al carrello

Immagini fornite dal venditore

Wei Qi Yan
ISBN 10: 3030610837 ISBN 13: 9783030610838
Nuovo Taschenbuch
Print on Demand

Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from graphical theory, mathematical models, and algorithmic implementation, as well as covers datasets preparation, programming, results analysis and evaluations.Beginning with a grounding about artificial neural networks with neurons and the activation functions, the work then explains the mechanism of deep learning using advanced mathematics. In particular, it emphasizes how to use TensorFlow and the latest MATLAB deep-learning toolboxes for implementing deep learning algorithms.As a prerequisite, readers should have a solid understanding especially of mathematical analysis, linear algebra, numerical analysis, optimizations, differential geometry, manifold, and information theory, as well as basic algebra, functional analysis, and graphical models. This computational knowledge will assist in comprehending the subject matter not only of this text/reference, but also in relevant deep learning journal articles and conference papers.This textbook/guide is aimed at Computer Science research students and engineers, as well as scientists interested in deep learning for theoretic research and analysis. More generally, this book is also helpful for those researchers who are interested in machine intelligence, pattern analysis, natural language processing, and machine vision.Dr. Wei Qi Yanis an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title,Visual Cryptography for Image Processing and Security. 152 pp. Englisch. Codice articolo 9783030610838

Contatta il venditore

Compra nuovo

EUR 64,19
Convertire valuta
Spese di spedizione: EUR 11,00
Da: Germania a: Italia
Destinazione, tempi e costi

Quantità: 2 disponibili

Aggiungi al carrello

Immagini fornite dal venditore

Wei Qi Yan
ISBN 10: 3030610837 ISBN 13: 9783030610838
Nuovo Taschenbuch

Da: AHA-BUCH GmbH, Einbeck, Germania

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from graphical theory, mathematical models, and algorithmic implementation, as well as covers datasets preparation, programming, results analysis and evaluations.Beginning with a grounding about artificial neural networks with neurons and the activation functions, the work then explains the mechanism of deep learning using advanced mathematics. In particular, it emphasizes how to use TensorFlow and the latest MATLAB deep-learning toolboxes for implementing deep learning algorithms.As a prerequisite, readers should have a solid understanding especially of mathematical analysis, linear algebra, numerical analysis, optimizations, differential geometry, manifold, and information theory, as well as basic algebra, functional analysis, and graphical models. This computational knowledge will assist in comprehending the subject matter not only of this text/reference, but also in relevant deep learning journal articles and conference papers.This textbook/guide is aimed at Computer Science research students and engineers, as well as scientists interested in deep learning for theoretic research and analysis. More generally, this book is also helpful for those researchers who are interested in machine intelligence, pattern analysis, natural language processing, and machine vision.Dr. Wei Qi Yanis an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title,Visual Cryptography for Image Processing and Security. Codice articolo 9783030610838

Contatta il venditore

Compra nuovo

EUR 64,19
Convertire valuta
Spese di spedizione: EUR 14,99
Da: Germania a: Italia
Destinazione, tempi e costi

Quantità: 1 disponibili

Aggiungi al carrello

Immagini fornite dal venditore

Wei Qi Yan
ISBN 10: 3030610837 ISBN 13: 9783030610838
Nuovo Taschenbuch

Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Taschenbuch. Condizione: Neu. Neuware -Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from graphical theory, mathematical models, and algorithmic implementation, as well as covers datasets preparation, programming, results analysis and evaluations.Beginning with a grounding about artificial neural networks with neurons and the activation functions, the work then explains the mechanism of deep learning using advanced mathematics. In particular, it emphasizes how to use TensorFlow and the latest MATLAB deep-learning toolboxes for implementing deep learning algorithms.As a prerequisite, readers should have a solid understanding especially of mathematical analysis, linear algebra, numerical analysis, optimizations, differential geometry, manifold, and information theory, as well as basic algebra, functional analysis, and graphical models. This computational knowledge will assist in comprehending the subject matter not only of this text/reference, but also in relevant deep learning journal articles and conference papers.This textbook/guide is aimed at Computer Science research students and engineers, as well as scientists interested in deep learning for theoretic research and analysis. More generally, this book is also helpful for those researchers who are interested in machine intelligence, pattern analysis, natural language processing, and machine vision.Dr. Wei Qi Yan is an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title, Visual Cryptography for Image Processing and Security.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 152 pp. Englisch. Codice articolo 9783030610838

Contatta il venditore

Compra nuovo

EUR 64,19
Convertire valuta
Spese di spedizione: EUR 15,00
Da: Germania a: Italia
Destinazione, tempi e costi

Quantità: 2 disponibili

Aggiungi al carrello

Foto dell'editore

Yan, Wei Qi
Editore: Springer, 2021
ISBN 10: 3030610837 ISBN 13: 9783030610838
Nuovo Brossura

Da: Ria Christie Collections, Uxbridge, Regno Unito

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Condizione: New. In. Codice articolo ria9783030610838_new

Contatta il venditore

Compra nuovo

EUR 71,14
Convertire valuta
Spese di spedizione: EUR 10,36
Da: Regno Unito a: Italia
Destinazione, tempi e costi

Quantità: Più di 20 disponibili

Aggiungi al carrello

Foto dell'editore

Wei Qi Yan
Editore: Springer 2021-12-05, 2021
ISBN 10: 3030610837 ISBN 13: 9783030610838
Nuovo Paperback

Da: Chiron Media, Wallingford, Regno Unito

Valutazione del venditore 4 su 5 stelle 4 stelle, Maggiori informazioni sulle valutazioni dei venditori

Paperback. Condizione: New. Codice articolo 6666-IUK-9783030610838

Contatta il venditore

Compra nuovo

EUR 68,79
Convertire valuta
Spese di spedizione: EUR 23,04
Da: Regno Unito a: Italia
Destinazione, tempi e costi

Quantità: 10 disponibili

Aggiungi al carrello

Vedi altre 2 copie di questo libro

Vedi tutti i risultati per questo libro