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Hybrid Soft Computing for Image Segmentation (Paperback, Softcover reprint of the original 1st ed. 2016): Siddhartha... Hybrid Soft Computing for Image Segmentation (Paperback, Softcover reprint of the original 1st ed. 2016)
Siddhartha Bhattacharyya, Paramartha Dutta, Sourav De, Goran Klepac
R3,954 Discovery Miles 39 540 Ships in 10 - 15 working days

This book proposes soft computing techniques for segmenting real-life images in applications such as image processing, image mining, video surveillance, and intelligent transportation systems. The book suggests hybrids deriving from three main approaches: fuzzy systems, primarily used for handling real-life problems that involve uncertainty; artificial neural networks, usually applied for machine cognition, learning, and recognition; and evolutionary computation, mainly used for search, exploration, efficient exploitation of contextual information, and optimization. The contributed chapters discuss both the strengths and the weaknesses of the approaches, and the book will be valuable for researchers and graduate students in the domains of image processing and computational intelligence.

Hybrid Soft Computing for Image Segmentation (Hardcover, 1st ed. 2016): Siddhartha Bhattacharyya, Paramartha Dutta, Sourav De,... Hybrid Soft Computing for Image Segmentation (Hardcover, 1st ed. 2016)
Siddhartha Bhattacharyya, Paramartha Dutta, Sourav De, Goran Klepac
R4,204 Discovery Miles 42 040 Ships in 10 - 15 working days

This book proposes soft computing techniques for segmenting real-life images in applications such as image processing, image mining, video surveillance, and intelligent transportation systems. The book suggests hybrids deriving from three main approaches: fuzzy systems, primarily used for handling real-life problems that involve uncertainty; artificial neural networks, usually applied for machine cognition, learning, and recognition; and evolutionary computation, mainly used for search, exploration, efficient exploitation of contextual information, and optimization. The contributed chapters discuss both the strengths and the weaknesses of the approaches, and the book will be valuable for researchers and graduate students in the domains of image processing and computational intelligence.

Metaheuristic Approaches to Portfolio Optimization (Hardcover): Jhuma Ray, Anirban Mukherjee, Sadhan Kumar Dey, Goran Klepac Metaheuristic Approaches to Portfolio Optimization (Hardcover)
Jhuma Ray, Anirban Mukherjee, Sadhan Kumar Dey, Goran Klepac
R5,704 Discovery Miles 57 040 Ships in 10 - 15 working days

Control of an impartial balance between risks and returns has become important for investors, and having a combination of financial instruments within a portfolio is an advantage. Portfolio management has thus become very important for reaching a resolution in high-risk investment opportunities and addressing the risk-reward tradeoff by maximizing returns and minimizing risks within a given investment period for a variety of assets. Metaheuristic Approaches to Portfolio Optimization is an essential reference source that examines the proper selection of financial instruments in a financial portfolio management scenario in terms of metaheuristic approaches. It also explores common measures used for the evaluation of risks/returns of portfolios in real-life situations. Featuring research on topics such as closed-end funds, asset allocation, and risk-return paradigm, this book is ideally designed for investors, financial professionals, money managers, accountants, students, professionals, and researchers.

Metaheuristic Approaches to Portfolio Optimization (Paperback): Jhuma Ray, Anirban Mukherjee, Sadhan Kumar Dey, Goran Klepac Metaheuristic Approaches to Portfolio Optimization (Paperback)
Jhuma Ray, Anirban Mukherjee, Sadhan Kumar Dey, Goran Klepac
R4,349 Discovery Miles 43 490 Ships in 10 - 15 working days

Control of an impartial balance between risks and returns has become important for investors, and having a combination of financial instruments within a portfolio is an advantage. Portfolio management has thus become very important for reaching a resolution in high-risk investment opportunities and addressing the risk-reward tradeoff by maximizing returns and minimizing risks within a given investment period for a variety of assets. Metaheuristic Approaches to Portfolio Optimization is an essential reference source that examines the proper selection of financial instruments in a financial portfolio management scenario in terms of metaheuristic approaches. It also explores common measures used for the evaluation of risks/returns of portfolios in real-life situations. Featuring research on topics such as closed-end funds, asset allocation, and risk-return paradigm, this book is ideally designed for investors, financial professionals, money managers, accountants, students, professionals, and researchers.

Intelligent Analysis of Multimedia Information (Hardcover): Siddhartha Bhattacharyya, Hrishikesh Bhaumik, Sourav De, Goran... Intelligent Analysis of Multimedia Information (Hardcover)
Siddhartha Bhattacharyya, Hrishikesh Bhaumik, Sourav De, Goran Klepac
R6,299 Discovery Miles 62 990 Ships in 10 - 15 working days

Multimedia represents information in novel and varied formats. One of the most prevalent examples of continuous media is video. Extracting underlying data from these videos can be an arduous task. From video indexing, surveillance, and mining, complex computational applications are required to process this data. Intelligent Analysis of Multimedia Information is a pivotal reference source for the latest scholarly research on the implementation of innovative techniques to a broad spectrum of multimedia applications by presenting emerging methods in continuous media processing and manipulation. This book offers a fresh perspective for students and researchers of information technology, media professionals, and programmers.

Developing Churn Models Using Data Mining Techniques and Social Network Analysis (Hardcover): Goran Klepac, Robert Kopal, Leo... Developing Churn Models Using Data Mining Techniques and Social Network Analysis (Hardcover)
Goran Klepac, Robert Kopal, Leo Mri?1/2i
R5,201 Discovery Miles 52 010 Ships in 10 - 15 working days

Churn prediction, recognition, and mitigation have become essential topics in various industries. As a means for forecasting and manageing risk, further research in this field can greatly assist companies in making informed decisions based on future possible scenarios. Developing Churn Models Using Data Mining Techniques and Social Network Analysis provides an in-depth analysis of attrition modeling relevant to business planning and management. Through its insightful and detailed explanation of best practices, tools, and theory surrounding churn prediction and the integration of analytics tools, this publication is especially relevant to managers, data specialists, business analysts, academicians, and upper-level students.

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