Metaheuristics for Medicine and Biology [electronic resource] / edited by Amir Nakib, El-Ghazali Talbi.
Contributor(s): Nakib, Amir [editor.]
| Talbi, El-Ghazali [editor.] | SpringerLink (Online service).
Material type: 
BookSeries: Studies in Computational Intelligence: 704Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: XVIII, 211 p. 120 illus., 67 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783662544280.Subject(s): Computational intelligence | Biomedical engineering | Artificial intelligence | Computational Intelligence | Biomedical Engineering and Bioengineering | Artificial IntelligenceAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
In:
Springer Nature eBookSummary: This book highlights recent research on metaheuristics for biomedical engineering, addressing both theoretical and applications aspects. Given the multidisciplinary nature of bio-medical image analysis, it has now become one of the most central topics in computer science, computer engineering and electrical and electronic engineering, and attracted the interest of many researchers. To deal with these problems, many traditional and recent methods, algorithms and techniques have been proposed. Among them, metaheuristics is the most common choice. This book provides essential content for senior and young researchers interested in methodologies for implementing metaheuristics to help solve biomedical engineering problems.
This book highlights recent research on metaheuristics for biomedical engineering, addressing both theoretical and applications aspects. Given the multidisciplinary nature of bio-medical image analysis, it has now become one of the most central topics in computer science, computer engineering and electrical and electronic engineering, and attracted the interest of many researchers. To deal with these problems, many traditional and recent methods, algorithms and techniques have been proposed. Among them, metaheuristics is the most common choice. This book provides essential content for senior and young researchers interested in methodologies for implementing metaheuristics to help solve biomedical engineering problems.
There are no comments for this item.