Deep Learning: Algorithms and Applications

Witold Pedrycz, Shyi-Ming Chen (Herausgeber)

Buch | Hardcover

XII, 360 Seiten

2019
Springer International Publishing (Verlag)
978-3-030-31759-1 (ISBN)

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This 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.

Preface.- Chapter 1. Activation Functions.- Chapter 2. Adversarial Examples in Deep Neural Networks: An Overview.- Chapter 3. Representation Learning in Power Time Series Forecasting, etc.

Erscheinungsdatum	06.11.2019
Reihe/Serie	Studies in Computational Intelligence
Zusatzinfo	XII, 360 p. 171 illus., 139 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	723 g
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
Themenwelt	Technik
Schlagworte	AI • Computational Intelligence • computer vision • Deep Learning Architectures • Development Paradigms • Image Processing • Knowledge Representation • machine learning • Natural Language Processing • pattern recognition
ISBN-10	3-030-31759-5 / 3030317595
ISBN-13	978-3-030-31759-1 / 9783030317591
Zustand	Neuware