Deep Learning: Algorithms and Applications

1. Auflage 2020
ISBN: 978-3-030-31759-1
Verlag: Springer International Publishing

Buch, Englisch, Band 865, 360 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 723 g

Reihe: Studies in Computational Intelligence

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.

Zielgruppe

Research

Autoren/Hrsg.

Chen, Shyi-Ming

Pedrycz, Witold

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

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.