Development and Analysis of Deep Learning Architectures

Development and Analysis of Deep Learning Architectures
  • eBook:
    Development and Analysis of Deep Learning Architectures
  • Author:
    Witold Pedrycz, Shyi-Ming Chen
  • Edition:
    1st ed. 2020 edition
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  • ISBN:
  • ISBN-13:
  • Language:
  • Pages:
  • Format:
    PDF, ePUB

Book Description
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.


Direct Error Driven Learning for Classification in Applications Generating Big-Data
Deep Learning for Soft Sensor Design
Case Study: Deep Convolutional Networks in Healthcare
Deep Domain Adaptation for Regression
Deep Learning-Based Pedestrian Detection for Automated Driving: Achievements and Future Challenges
Deep Learning in Speaker Recognition
Baby Cry Detection: Deep Learning and Classical Approaches
Securing Industrial Control Systems from False Data Injection Attacks with Convolutional Neural Networks
Deep Learning for Wireless Communications
Identifying Extremism in Text Using Deep Learning

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