Bio-Inspired Computation and Applications in Image Processing

Xin-She Yang

ISBN 10: 0128045361 / ISBN 13: 9780128045367

Published by Elsevier Science & Technology, Academic Press Aug 2016, 2016

About this Item

Neuware - Bio-Inspired Computation and Applications in Image Processing summarizes the latest developments in bio-inspired computation in image processing, focusing on nature-inspired algorithms that are linked with deep learning, such as ant colony optimization, particle swarm optimization, and bat and firefly algorithms that have recently emerged in the field. In addition to documenting state-of-the-art developments, this book also discusses future research trends in bio-inspired computation, helping researchers establish new research avenues to pursue.

Seller Inventory # 9780128045367

Bibliographic Details

• Title: Bio-Inspired Computation and Applications in Image Processing
• Publisher: Elsevier Science & Technology, Academic Press Aug 2016
• Publication Date: 2016
• Language: English
• ISBN 10: 0128045361
• ISBN 13: 9780128045367
• Binding: Buch
• Condition: Neu
• Dimensions: 234W x 190H x 35D millimeters 234 millimeters width by 190 millimeters height by 35 millimeters depth
• Weight: 700 grams

About this title

Synopsis

Bio-Inspired Computation and Applications in Image Processing summarizes the latest developments in bio-inspired computation in image processing, focusing on nature-inspired algorithms that are linked with deep learning, such as ant colony optimization, particle swarm optimization, and bat and firefly algorithms that have recently emerged in the field.

In addition to documenting state-of-the-art developments, this book also discusses future research trends in bio-inspired computation, helping researchers establish new research avenues to pursue.

• Reviews the latest developments in bio-inspired computation in image processing
• Focuses on the introduction and analysis of the key bio-inspired methods and techniques
• Combines theory with real-world applications in image processing
• Helps solve complex problems in image and signal processing
• Contains a diverse range of self-contained case studies in real-world applications

About the Authors

Xin-She Yang obtained his DPhil in Applied Mathematics from the University of Oxford. He then worked at Cambridge University and National Physical Laboratory (UK) as a Senior Research Scientist. He is currently a Reader in Modelling and Simulation at Middlesex University London, Fellow of the Institute of Mathematics and its Application (IMA) and a Book Series Co-Editor of the Springer Tracts in Nature-Inspired Computing. He has published more than 25 books and more than 400 peer-reviewed research publications with over 82000 citations, and he has been on the prestigious list of highly cited researchers (Web of Sciences) for seven consecutive years (2016-2022).

Joao Paulo Papa obtained his Ph.D. in Computer Science from University of Campinas, Brazil, in 2008, and was a visiting scholar at Harvard University from 2014-2015. He has been a Professor at Sao Paulo State University (UNESP), Brazil, since 2009, and his main interests include image processing, machine learning and meta-heuristic optimization.