Siddhartha Bhattacharyya Livres

Focusing on optimization problems, this book delves into metaheuristics, which are advanced procedures for choosing search algorithms that can effectively navigate challenges with incomplete or imperfect information. It explores the principles and applications of these techniques, providing insights into their role in achieving efficient solutions.

International experts discuss different hybrid metaheuristic techniques to analyze images in depth. The hybrid metaheuristic approach delivers efficient methods of image analysis especially useful for industrial research. The book illustrates the mo

This book introduces the most recent research and innovative developments regarding the new strains of COVID-19. While medical and natural sciences have been working instantly on deriving solutions and trying to protect humankind against such virus types, there is also a great focus on technological developments for improving the mechanism – momentum of science for effective and efficient solutions. At this point, computational intelligence is the most powerful tools for researchers to fight against COVID-19. Thanks to instant data-analyze and predictive techniques by computational intelligence, it is possible to get positive results and introduce revolutionary solutions against related medical diseases. By running capabilities – resources for rising the computational intelligence, technological fields like Artificial Intelligence (with Machine / Deep Learning), Data Mining, Applied Mathematics are essential components for processing data, recognizing patterns, modelling new techniques and improving the advantages of the computational intelligence more. Nowadays, there is a great interest in the application potentials of computational intelligence to be an effective approach for taking humankind more step away, after COVID-19 and before pandemics similar to the COVID-19 many appear.

This volume features eight chapters focused on the latest findings in intelligent multimedia data analysis. Multimedia data, encompassing various forms such as text, audio, images, videos, and animations, often involves at least one continuous media type. The diversity of these formats leads to uncertainties and imprecision that traditional computing methods struggle to address. Soft computing technologies effectively manage this imprecision and uncertainty, making them suitable for processing real-world information. Analyzing multimedia data has significant applications in areas like medical diagnosis, video surveillance, and text annotation. This work serves as a reference for undergraduate and postgraduate students in computer science, electronics and telecommunication, information science, and electrical engineering. The series aims to provide a comprehensive overview of cutting-edge research in computational intelligence, fostering scholarly discourse on advances in artificial life and machine learning, including metaheuristics, approximate reasoning, and robotics. As the field evolves, particularly with new machine learning algorithms, this series unites leading researchers dedicated to advancing knowledge and understanding of the latest developments in engineering and technology.

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.

Proper analysis of image and multimedia data requires efficient extraction and segmentation techniques. Among the many computational intelligence approaches, the soft computing paradigm is best equipped with several tools and techniques that incorporate intelligent concepts and principles. This book is dedicated to object extraction, image segmentation, and edge detection using soft computing techniques with extensive real-life application to image and multimedia data. The authors start with a comprehensive tutorial on the basics of brain structure and learning, and then the key soft computing techniques, including evolutionary computation, neural networks, fuzzy sets and fuzzy logic, and rough sets. They then present seven chapters that detail the application of representative techniques to complex image processing tasks such as image recognition, lighting control, target tracking, object extraction, and edge detection. These chapters follow a structured approach with detailed explanations of the problems, solutions, results, and conclusions. This is both a standalone textbook for graduates in computer science, electrical engineering, system science, and information technology, and a reference for researchers and engineers engaged with pattern recognition, image processing, and soft computing.