Bio-Inspired Computation and Applications in Image Processing - 1st Edition - ISBN: 9780128045367, 9780128045374

Bio-Inspired Computation and Applications in Image Processing

1st Edition

Authors: Xin-She Yang João Papa
eBook ISBN: 9780128045374
Hardcover ISBN: 9780128045367
Imprint: Academic Press
Published Date: 5th August 2016
Page Count: 374
Tax/VAT will be calculated at check-out Price includes VAT (GST)
30% off
30% off
30% off
30% off
30% off
20% off
20% off
30% off
30% off
30% off
30% off
30% off
20% off
20% off
30% off
30% off
30% off
30% off
30% off
20% off
20% off
30% off
30% off
30% off
30% off
30% off
20% off
20% off
150.00
105.00
105.00
105.00
105.00
105.00
120.00
120.00
108.00
75.60
75.60
75.60
75.60
75.60
86.40
86.40
95.00
66.50
66.50
66.50
66.50
66.50
76.00
76.00
160.86
112.60
112.60
112.60
112.60
112.60
128.69
128.69
Unavailable
Price includes VAT (GST)
× DRM-Free

Easy - Download and start reading immediately. There’s no activation process to access eBooks; all eBooks are fully searchable, and enabled for copying, pasting, and printing.

Flexible - Read on multiple operating systems and devices. Easily read eBooks on smart phones, computers, or any eBook readers, including Kindle.

Open - Buy once, receive and download all available eBook formats, including PDF, EPUB, and Mobi (for Kindle).

Institutional Access

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.

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.

Key Features

  • 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

Readership

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

Table of Contents

Chapter 1. Bio-Inspired Computation and its Applications in Image Processing: An Overview
Chapter 2. Fine-Tuning Enhanced Probabilistic Neural Networks Using Meta-heuristic-driven Optimization
Chapter 3. Fine-Tuning Deep Belief Networks using Cuckoo Search
Chapter 4. Improved Weighted Thresholded Histogram Equalization Algorithm for Digital Image Contrast Enhancement Using Bat Algorithm
Chapter 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 processing
Chapter 9. Multi-temporal remote sensing image registration by nature inspired techniques
Chapter 10. Firefly Algorithm for Optimized Non-Rigid Demons Registration
Chapter 11. Minimizing the Mode-Change Latency in Real-Time Image Processing Applications
Chapter 12. Learning OWA Filters parameters for SAR Imagery with multiple polarizations
Chapter 13. Oil Reservoir Quality Assisted by Machine learning and Evolutionary Computation
Chapter 14. Solving Imbalanced Dataset Problems for High Dimensional Image Processing by Swarm Optimization
Chapter 15. Rivas: The Automated Retinal Image analysis Software

Details

No. of pages:
374
Language:
English
Copyright:
© Academic Press 2016
Published:
Imprint:
Academic Press
eBook ISBN:
9780128045374
Hardcover ISBN:
9780128045367

About the Author

Xin-She  Yang

Xin-She Yang

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).

Affiliations and Expertise

School of Science and Technology, Middlesex University, UK

João  Papa

João Papa

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.

Affiliations and Expertise

Assistant professor, Sao Paulo State University (UNESP), Brazil; Visiting scholar, Harvard University, Cambridge, MA, USA