Deep Learning: Algorithms and Applications
Editors: Pedrycz, Witold, Chen, Shyi-Ming (Eds.)
Free Preview- Provides a comprehensive and up-to-date overview of deep learning by discussing a range of methodological and algorithmic issues
- Addresses implementations and case studies, identifying the best design practices and assessing business models and methodologies encountered in industry, health care, science, administration, and business
- Serves as a unique and well-structured reference resource for graduate and senior undergraduate students in areas such as computational intelligence, pattern recognition, computer vision, knowledge acquisition and representation, and knowledge-based systems
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- About this book
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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.
- Table of contents (11 chapters)
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Activation Functions
Pages 1-30
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Adversarial Examples in Deep Neural Networks: An Overview
Pages 31-65
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Representation Learning in Power Time Series Forecasting
Pages 67-101
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Deep Learning Application: Load Forecasting in Big Data of Smart Grids
Pages 103-128
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Fast and Accurate Seismic Tomography via Deep Learning
Pages 129-156
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Table of contents (11 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Deep Learning: Algorithms and Applications
- Editors
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- Witold Pedrycz
- Shyi-Ming Chen
- Series Title
- Studies in Computational Intelligence
- Series Volume
- 865
- Copyright
- 2020
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer Nature Switzerland AG
- eBook ISBN
- 978-3-030-31760-7
- DOI
- 10.1007/978-3-030-31760-7
- Hardcover ISBN
- 978-3-030-31759-1
- Softcover ISBN
- 978-3-030-31762-1
- Series ISSN
- 1860-949X
- Edition Number
- 1
- Number of Pages
- XII, 360
- Number of Illustrations
- 32 b/w illustrations, 139 illustrations in colour
- Topics
