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Computational Methods for Deep Learning

Theory, Algorithms, and Implementations
BuchGebunden
222 Seiten
Englisch
Springererschienen am16.09.20232. Aufl.
Through the second edition, this book showcases how computational methods in deep learning serve as a dynamic driving force in this era of artificial intelligence (AI). This book is intended for research students, engineers, as well as computer scientists with interest in computational methods in deep learning.mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR64,19
BuchGebunden
EUR90,94
E-BookPDF1 - PDF WatermarkE-Book
EUR64,19
E-BookPDF1 - PDF WatermarkE-Book
EUR90,94

Produkt

KlappentextThrough the second edition, this book showcases how computational methods in deep learning serve as a dynamic driving force in this era of artificial intelligence (AI). This book is intended for research students, engineers, as well as computer scientists with interest in computational methods in deep learning.
Details
ISBN/GTIN978-981-99-4822-2
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2023
Erscheinungsdatum16.09.2023
Auflage2. Aufl.
ReiheTexts in Computer Science
Seiten222 Seiten
SpracheEnglisch
IllustrationenXX, 222 p. 40 illus., 36 illus. in color.
Artikel-Nr.54116647

Inhalt/Kritik

Inhaltsverzeichnis
1. Introduction.-  2. Deep Learning Platforms.- 3.  CNN and RNN.- 4. Autoencoder and GAN.- 5. Reinforcement Learning.- 6. CapsNet and Manifold Learning.- 7. Boltzmann Machines.- 8. Transfer Learning and Ensemble Learning.mehr

Schlagworte

Autor

Wei Qi Yan is Director of Institute of Robotics & Vision (IoRV) at Auckland University of Technology (AUT) in New Zealand (NZ). Dr. Yan's research interests encompass deep learning, intelligent surveillance, computer vision, and multimedia computing. His expertise lies in computational mathematics, applied mathematics, computer science, and computer engineering. He holds the positions of Chief Technology Officer (CTO) of Screen 2 Script Limited (NZ) and Director and Chief Scientist of the Joint Laboratory between AUT and Shandong Academy of Sciences China (NZ). Dr. Yan also serves as Chair of ACM Multimedia Chapter of New Zealand and is Member of the ACM. Additionally, he is Senior Member of the IEEE and TC Member of the IEEE. In 2022, Dr. Yan was recognized as one of the world's top 2% cited scientists by Stanford University.