Advances in Soft Computing and Machine Learning in Image Processing

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 a...

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Bibliographic Details
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing, 2018.
Edition:1st ed. 2018.
Series:Studies in Computational Intelligence, 730
Subjects:
ISBN:9783319637549
ISSN:1860-949X ;
Online Access: Get full text
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040 |a Springer-Nature  |b eng  |c CVTISR  |e AACR2 
041 |a eng 
245 1 0 |a Advances in Soft Computing and Machine Learning in Image Processing  |h [electronic resource] /  |c edited by Aboul Ella Hassanien, Diego Alberto Oliva. 
250 |a 1st ed. 2018. 
260 1 |a Cham :  |b Springer International Publishing,  |c 2018. 
300 |a XII, 718 p. 309 illus., 195 illus. in color.  |b online resource. 
490 1 |a Studies in Computational Intelligence,  |x 1860-949X ;  |v 730 
500 |a Engineering  
505 0 |a Color Spaces Advantages and Disadvantages in Image Color Clustering Segmentation -- Multi-objective Whale Optimization Algorithm for Multi-level Thresholding Segmentation -- Evaluating Swarm Optimization Algorithms for Segmentation of Liver Images -- Thermal Image Segmentation Using Evolutionary Computation Techniques -- News Videos Segmentation Using Dominant Colors Representation. 
516 |a text file PDF 
520 |a 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. 
650 0 |a Computational intelligence. 
650 0 |a Artificial intelligence. 
650 0 |a Signal processing. 
650 0 |a Image processing. 
650 0 |a Speech processing systems. 
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