Bio-Inspired Computation and Applications in Image Processing
Autor Xin She Yang, João Paulo Papaen Limba Engleză Hardback – 4 aug 2016
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
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Specificații
ISBN-13: 9780128045367
ISBN-10: 0128045361
Pagini: 374
Dimensiuni: 191 x 235 x 24 mm
Greutate: 1.02 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 0128045361
Pagini: 374
Dimensiuni: 191 x 235 x 24 mm
Greutate: 1.02 kg
Editura: ELSEVIER SCIENCE
Public țintă
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.Cuprins
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