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.
Format:
CONTRIBUTORS: Xin-She Yang, Joao Paulo Papa
EAN: 9780128045367
COUNTRY: United States
PAGES:
WEIGHT: 700 g
HEIGHT: 235 cm
PUBLISHED BY: Elsevier Science Publishing Co Inc
DATE PUBLISHED: 2016-08-05
CITY:
GENRE: COMPUTERS / Software Development & Engineering / Computer Graphics, COMPUTERS / Image Processing, COMPUTERS / Design, Graphics & Media / Photography, PHOTOGRAPHY / Techniques / Digital
WIDTH: 191 cm
SPINE:
Book Themes:
Photographic equipment and techniques: general, Graphical and digital media applications, Photo and image editing, Image processing
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 at Middlesex University London, Adjunct Professor at Reykjavik University (Iceland) and Guest Professor at Xi’an Polytechnic University (China). He is an elected Bye-Fellow at Downing College, Cambridge University. He is also the IEEE CIS Chair for the Task Force on Business Intelligence and Knowledge Management, and the Editor-in-Chief of International Journal of Mathematical Modelling and Numerical Optimisation (IJMMNO). 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.