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Applications of Hybrid Metaheuristic Algorithms for Image Processing

  • Book
  • © 2020


  • Presents the latest tools used for image processing and hybrid metaheuristic algorithms
  • Focuses on the theory and application of metaheuristic algorithms for segmentation of images from different sources
  • Discusses recent research on and applications of hybrid metaheuristic algorithms for image processing

Part of the book series: Studies in Computational Intelligence (SCI, volume 890)

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Table of contents (22 chapters)

  1. Hybrid Metaheuristics and Image Segmentation

  2. Hybrid Metaheuristics and Other Image Processing Tasks

  3. Health Applications


About this book

This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects using complex approaches and medical applications. The book also discusses the theory of the methodologies used to provide an overview of the applications of these tools in image processing.

The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence. Further, it is a valuable resource for researchers from the evolutionary computation, artificial intelligence and image processing communities.

Editors and Affiliations

  • CUCEI, University of Guadalajara, Guadajalara, Mexico

    Diego Oliva, Salvador Hinojosa

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