This book offers a timely reflection on the remarkable range of algorithms and applications that have made the area of deep learning so attractive and heavily researched today. Introducing the diversity of learning mechanisms in the environment of big data, and presenting authoritative studies in fi
Development and Analysis of Deep Learning Architectures
β Scribed by Witold Pedrycz, Shyi-Ming Chen
- Publisher
- Springer International Publishing
- Year
- 2020
- Tongue
- English
- Leaves
- 296
- Series
- Studies in Computational Intelligence 867
- Edition
- 1st ed. 2020
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This book offers a timely reflection on the remarkable range of algorithms and applications that have made the area of deep learning so attractive and heavily researched today. Introducing the diversity of learning mechanisms in the environment of big data, and presenting authoritative studies in fields such as sensor design, health care, autonomous driving, industrial control and wireless communication, it enables readers to gain a practical understanding of design. The book also discusses systematic design procedures, optimization techniques, and validation processes.
β¦ Table of Contents
Front Matter ....Pages i-xi
Direct Error Driven Learning for Classification in Applications Generating Big-Data (R. Krishnan, S. Jagannathan, V. A. Samaranayake)....Pages 1-29
Deep Learning for Soft Sensor Design (Salvatore Graziani, Maria Gabriella Xibilia)....Pages 31-59
Case Study: Deep Convolutional Networks in Healthcare (Mutlu Avci, Mehmet SarΔ±gΓΌl, Buse Melis Ozyildirim)....Pages 61-89
Deep Domain Adaptation for Regression (Ankita Singh, Shayok Chakraborty)....Pages 91-115
Deep Learning-Based Pedestrian Detection for Automated Driving: Achievements and Future Challenges (Michelle Karg, Christian Scharfenberger)....Pages 117-143
Deep Learning in Speaker Recognition (Omid Ghahabi, Pooyan Safari, Javier Hernando)....Pages 145-169
Baby Cry Detection: Deep Learning and Classical Approaches (Rami Cohen, Dima Ruinskiy, Janis Zickfeld, Hans IJzerman, Yizhar Lavner)....Pages 171-196
Securing Industrial Control Systems from False Data Injection Attacks with Convolutional Neural Networks (Sasanka Potluri, Shamim Ahmed, Christian Diedrich)....Pages 197-222
Deep Learning for Wireless Communications (Tugba Erpek, Timothy J. OβShea, Yalin E. Sagduyu, Yi Shi, T. Charles Clancy)....Pages 223-266
Identifying Extremism in Text Using Deep Learning (Andrew Johnston, Angjelo Marku)....Pages 267-289
Back Matter ....Pages 291-292
β¦ Subjects
Engineering; Computational Intelligence
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