Deep learning : algorithms and applications / Witold Pedrycz, Shyi-Ming Chen, editors.

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Deep learning : algorithms and applications / Witold Pedrycz, Shyi-Ming Chen, editors.

9783030317607 (electronic book)
3030317609 (electronic book)
9783030317591
3030317595

https://doi.org/10.1007/978-3-030-31760-7
https://doi.org/10.1007/978-3-030-31

Cham, Switzerland : Springer, [2020].

English

1 online resource (xii, 360 pages) : illustrations.

10.1007/978-3-030-31760-7 doi
10.1007/978-3-030-31

Q325.5

006.3/1

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 paradigms 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.

Includes bibliographical references and index.

Access limited to authorized users.

Online resource; title from PDF title page (SpringerLink, viewed October 31, 2019).

Studies in computational intelligence ; v. 865.

Print version: 9783030317591

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