Bio-Inspired Computation and Applications in Image Processing
Published on 5. August 2016
Book
Hardback
374 pages
978-0-12-804536-7 (ISBN)
Description
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.
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.
More details
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
Graduates and PhD students and lecturers in electronic engineering, image processing, signal processing, data science and applied science. Researchers and engineers as well as experienced experts.
Dimensions
Height: 235 mm
Width: 191 mm
Weight
700 gr
ISBN-13
978-0-12-804536-7 (9780128045367)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Xin-She Yang | João Paulo Papa
Bio-Inspired Computation and Applications in Image Processing
E-Book
08/2016
Academic Press
€108.00
Available for download
Persons
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.
Content
Chapter 1. Bio-Inspired Computation and its Applications in Image Processing: An OverviewChapter 2. Fine-Tuning Enhanced Probabilistic Neural Networks Using Meta-heuristic-driven OptimizationChapter 3. Fine-Tuning Deep Belief Networks using Cuckoo SearchChapter 4. Improved Weighted Thresholded Histogram Equalization Algorithm for Digital Image Contrast Enhancement Using Bat AlgorithmChapter 5. Ground Glass Opacity Nodules Detection and Segmentation using Snake Model Chapter 6. Mobile Object Tracking Using Cuckoo Search Chapter 7. Towards Optimal Watermarking of Grayscale Images Using Multiple Scaling Factor based Cuckoo Search Technique Chapter 8. Bat algorithm based automatic clustering method and its application in image processingChapter 9. Multi-temporal remote sensing image registration by nature inspired techniques Chapter 10. Firefly Algorithm for Optimized Non-Rigid Demons RegistrationChapter 11. Minimizing the Mode-Change Latency in Real-Time Image Processing ApplicationsChapter 12. Learning OWA Filters parameters for SAR Imagery with multiple polarizationsChapter 13. Oil Reservoir Quality Assisted by Machine learning and Evolutionary Computation Chapter 14. Solving Imbalanced Dataset Problems for High Dimensional Image Processing by Swarm OptimizationChapter 15. Rivas: The Automated Retinal Image analysis Software