Advances in Soft Computing and Machine Learning in Image Processing [electronic resource] /

Contributor(s):

Language: ENG Series: Studies in Computational Intelligence ; 730Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018Description: XII, 718 p. 309 illus., 195 illus. in color. | Binding - Card Paper |Content type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783319637549

Subject(s):

Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:

006.3 23

Online resources:

Click here to access eBook in Springer Nature platform. (Within Campus only.)

In: Springer Nature eBookSummary: This book is a collection of the latest applications of methods from soft computing and machine learning in image processing. It explores different areas ranging from image segmentation to the object recognition using complex approaches, and includes the theory of the methodologies used to provide an overview of the application of these tools in image processing. The material has been compiled from a scientific perspective, and the book is primarily intended for undergraduate and postgraduate science, engineering, and computational mathematics students. It can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence, and is a valuable resource for researchers in the evolutionary computation, artificial intelligence and image processing communities.

List(s) this item appears in: Springer Nature eBooks

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This book is a collection of the latest applications of methods from soft computing and machine learning in image processing. It explores different areas ranging from image segmentation to the object recognition using complex approaches, and includes the theory of the methodologies used to provide an overview of the application of these tools in image processing. The material has been compiled from a scientific perspective, and the book is primarily intended for undergraduate and postgraduate science, engineering, and computational mathematics students. It can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence, and is a valuable resource for researchers in the evolutionary computation, artificial intelligence and image processing communities.

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