Bio-Inspired Computation and Applications in Image Processing [Hardcover]

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

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 l+