國立虎尾科技大學 |

Hybrid metaheuristics for image analysis

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Hybrid metaheuristics for image analysis/ edited by Siddhartha Bhattacharyya.
其他作者:	Bhattacharyya, Siddhartha.
出版者:	Cham :Springer International Publishing : : 2018.,
面頁冊數:	xii, 256 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Image analysis. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-77625-5
ISBN:	9783319776255

Hybrid metaheuristics for image analysis
Hybrid metaheuristics for image analysis[electronic resource] /edited by Siddhartha Bhattacharyya. - Cham :Springer International Publishing :2018. - xii, 256 p. :ill., digital ;24 cm.

Current and Future Trends in Segmenting Satellite Images Using Hybrid and Dynamic Genetic Algorithms -- A Hybrid Metaheuristic Algorithm Based on Quantum Genetic Computing for Image Segmentation -- Genetic Algorithm Implementation to Optimize the Hybridization of Feature Extraction and Metaheuristic Classifiers -- Optimization of a HMM-Based Hand Gesture Recognition System Using a Hybrid Cuckoo Search Algorithm -- Satellite Image Contrast Enhancement Using Fuzzy Termite Colony Optimization -- Image Segmentation Using Metaheuristic-Based DeformableModels -- Hybridization of the Univariate Marginal Distribution Algorithm with Simulated Annealing for Parametric Parabola Detection -- Image Thresholding Based on Fuzzy Particle Swarm Optimization -- Hybrid Metaheuristics Applied to Image Reconstruction for an Electrical Impedance Tomography Prototype.

This book presents contributions in the field of computational intelligence for the purpose of image analysis. The chapters discuss how problems such as image segmentation, edge detection, face recognition, feature extraction, and image contrast enhancement can be solved using techniques such as genetic algorithms and particle swarm optimization. The contributions provide a multidimensional approach, and the book will be useful for researchers in computer science, electrical engineering, and information technology.

ISBN: 9783319776255

Standard No.: 10.1007/978-3-319-77625-5doiSubjects--Topical Terms:

578867
Image analysis.

LC Class. No.: TA1637 / .H93 2018

Dewey Class. No.: 621.367

Hybrid metaheuristics for image analysis
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505 0 $a Current and Future Trends in Segmenting Satellite Images Using Hybrid and Dynamic Genetic Algorithms -- A Hybrid Metaheuristic Algorithm Based on Quantum Genetic Computing for Image Segmentation -- Genetic Algorithm Implementation to Optimize the Hybridization of Feature Extraction and Metaheuristic Classifiers -- Optimization of a HMM-Based Hand Gesture Recognition System Using a Hybrid Cuckoo Search Algorithm -- Satellite Image Contrast Enhancement Using Fuzzy Termite Colony Optimization -- Image Segmentation Using Metaheuristic-Based DeformableModels -- Hybridization of the Univariate Marginal Distribution Algorithm with Simulated Annealing for Parametric Parabola Detection -- Image Thresholding Based on Fuzzy Particle Swarm Optimization -- Hybrid Metaheuristics Applied to Image Reconstruction for an Electrical Impedance Tomography Prototype.
520 $a This book presents contributions in the field of computational intelligence for the purpose of image analysis. The chapters discuss how problems such as image segmentation, edge detection, face recognition, feature extraction, and image contrast enhancement can be solved using techniques such as genetic algorithms and particle swarm optimization. The contributions provide a multidimensional approach, and the book will be useful for researchers in computer science, electrical engineering, and information technology.
650 0 $a Image analysis. $3 578867
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650 0 $a Heuristic programming. $3 681151
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650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 671334
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