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Integrating Metaheuristics In Computer Vision For Real World Optimization Problems


Integrating Metaheuristics In Computer Vision For Real World Optimization Problems
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Integrating Metaheuristics In Computer Vision For Real World Optimization Problems


Integrating Metaheuristics In Computer Vision For Real World Optimization Problems
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Author : Shubham Mahajan
language : en
Publisher: John Wiley & Sons
Release Date : 2024-08-01

Integrating Metaheuristics In Computer Vision For Real World Optimization Problems written by Shubham Mahajan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-01 with Computers categories.


A comprehensive book providing high-quality research addressing challenges in theoretical and application aspects of soft computing and machine learning in image processing and computer vision. Researchers are working to create new algorithms that combine the methods provided by CI approaches to solve the problems of image processing and computer vision such as image size, noise, illumination, and security. The 19 chapters in this book examine computational intelligence (CI) approaches as alternative solutions for automatic computer vision and image processing systems in a wide range of applications, using machine learning and soft computing. Applications highlighted in the book include: diagnostic and therapeutic techniques for ischemic stroke, object detection, tracking face detection and recognition; computational-based strategies for drug repositioning and improving performance with feature selection, extraction, and learning; methods capable of retrieving photometric and geometric transformed images; concepts of trading the cryptocurrency market based on smart price action strategies; comparative evaluation and prediction of exoplanets using machine learning methods; the risk of using failure rate with the help of MTTF and MTBF to calculate reliability; a detailed description of various techniques using edge detection algorithms; machine learning in smart houses; the strengths and limitations of swarm intelligence and computation; how to use bidirectional LSTM for heart arrhythmia detection; a comprehensive study of content-based image-retrieval techniques for feature extraction; machine learning approaches to understanding angiogenesis; handwritten image enhancement based on neutroscopic-fuzzy. Audience The book has been designed for researchers, engineers, graduate, and post-graduate students wanting to learn more about the theoretical and application aspects of soft computing and machine learning in image processing and computer vision.



Integrating Metaheuristics In Computer Vision For Real World Optimization Problems


Integrating Metaheuristics In Computer Vision For Real World Optimization Problems
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Author : Shubham Mahajan
language : en
Publisher: John Wiley & Sons
Release Date : 2024-08-27

Integrating Metaheuristics In Computer Vision For Real World Optimization Problems written by Shubham Mahajan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-27 with Computers categories.


A comprehensive book providing high-quality research addressing challenges in theoretical and application aspects of soft computing and machine learning in image processing and computer vision. Researchers are working to create new algorithms that combine the methods provided by CI approaches to solve the problems of image processing and computer vision such as image size, noise, illumination, and security. The 19 chapters in this book examine computational intelligence (CI) approaches as alternative solutions for automatic computer vision and image processing systems in a wide range of applications, using machine learning and soft computing. Applications highlighted in the book include: diagnostic and therapeutic techniques for ischemic stroke, object detection, tracking face detection and recognition; computational-based strategies for drug repositioning and improving performance with feature selection, extraction, and learning; methods capable of retrieving photometric and geometric transformed images; concepts of trading the cryptocurrency market based on smart price action strategies; comparative evaluation and prediction of exoplanets using machine learning methods; the risk of using failure rate with the help of MTTF and MTBF to calculate reliability; a detailed description of various techniques using edge detection algorithms; machine learning in smart houses; the strengths and limitations of swarm intelligence and computation; how to use bidirectional LSTM for heart arrhythmia detection; a comprehensive study of content-based image-retrieval techniques for feature extraction; machine learning approaches to understanding angiogenesis; handwritten image enhancement based on neutroscopic-fuzzy. Audience The book has been designed for researchers, engineers, graduate, and post-graduate students wanting to learn more about the theoretical and application aspects of soft computing and machine learning in image processing and computer vision.



Integrating Meta Heuristics And Machine Learning For Real World Optimization Problems


Integrating Meta Heuristics And Machine Learning For Real World Optimization Problems
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Author : Essam Halim Houssein
language : en
Publisher: Springer Nature
Release Date : 2022-06-04

Integrating Meta Heuristics And Machine Learning For Real World Optimization Problems written by Essam Halim Houssein and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-04 with Technology & Engineering categories.


This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems. This book has exciting chapters that employ evolutionary and swarm optimization tools combined with machine learning techniques. The fields of applications are from distribution systems until medical diagnosis, and they are also included different surveys and literature reviews that will enrich the reader. Besides, cutting-edge methods such as neuroevolutionary and IoT implementations are presented in some chapters. In this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and can be used in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the material can be helpful for research from the evolutionary computation, artificial intelligence communities.



Computer Vision And Robotics


Computer Vision And Robotics
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Author : Praveen Kumar Shukla
language : en
Publisher: Springer Nature
Release Date : 2025-06-28

Computer Vision And Robotics written by Praveen Kumar Shukla and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-28 with Technology & Engineering categories.


This book consists of a collection of the high-quality research articles in the field of computer vision and robotics which are presented at the International Conference on Computer Vision and Robotics (CVR 2024), organized by Symbiosis Skills and Professional University, Pune, Maharashtra, India, during 25–26 May 2024. The book discusses applications of computer vision and robotics in the fields like medical science, defence, and smart city planning. The book presents recent works from researchers, academicians, industry, and policy makers.



Proceedings Of International Conference On Advanced Materials Manufacturing And Sustainable Development Icammsd 2024


Proceedings Of International Conference On Advanced Materials Manufacturing And Sustainable Development Icammsd 2024
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Author : B. Sridhar Babu
language : en
Publisher: Springer Nature
Release Date : 2025-03-13

Proceedings Of International Conference On Advanced Materials Manufacturing And Sustainable Development Icammsd 2024 written by B. Sridhar Babu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-13 with Technology & Engineering categories.


This open access proceedings volume provides the premier interdisciplinary forum for scientists, engineers, and practitioners to present their latest research results, ideas, developments, and applications in the area of manufacturing, advanced materials and sustainability. It covers inspiring breakthrough innovations from fundamentals to technological challenges and applications that are shaping the era of industry 4.0.



Nature Inspired Metaheuristic Algorithms


Nature Inspired Metaheuristic Algorithms
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Author : Sulabh Bansal
language : en
Publisher: CRC Press
Release Date : 2025-06-10

Nature Inspired Metaheuristic Algorithms written by Sulabh Bansal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-10 with Computers categories.


This comprehensive text provides practical guidance for implementing nature-inspired algorithms and metaheuristics in real-life scenarios to solve complex optimization problems. It further demonstrates how nature inspired metaheuristic algorithms have the potential to contribute to multiple United Nations sustainable development goals such as climate action, clean energy, and sustainable cities. This book: Discusses load balancing and demand response using nature-inspired optimization techniques Presents energy-efficient routing and scheduling, energy management, and optimization using metaheuristic algorithms Covers disease diagnosis, and prognosis using metaheuristic algorithms, drug discovery, and development using nature-inspired optimization techniques Explains waste reduction and recycling, image processing, and computer vision using nature-inspired optimization techniques Illustrates medical image analysis and segmentation using Ant Colony optimization, and Particle Swarm optimization techniques Nature-inspired Metaheuristic Algorithms is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.



Quantum Inspired Meta Heuristics For Image Analysis


Quantum Inspired Meta Heuristics For Image Analysis
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Author : Sandip Dey
language : en
Publisher: John Wiley & Sons
Release Date : 2019-06-03

Quantum Inspired Meta Heuristics For Image Analysis written by Sandip Dey and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-03 with Technology & Engineering categories.


Introduces quantum inspired techniques for image analysis for pure and true gray scale/color images in a single/multi-objective environment This book will entice readers to design efficient meta-heuristics for image analysis in the quantum domain. It introduces them to the essence of quantum computing paradigm, its features, and properties, and elaborates on the fundamentals of different meta-heuristics and their application to image analysis. As a result, it will pave the way for designing and developing quantum computing inspired meta-heuristics to be applied to image analysis. Quantum Inspired Meta-heuristics for Image Analysis begins with a brief summary on image segmentation, quantum computing, and optimization. It also highlights a few relevant applications of the quantum based computing algorithms, meta-heuristics approach, and several thresholding algorithms in vogue. Next, it discusses a review of image analysis before moving on to an overview of six popular meta-heuristics and their algorithms and pseudo-codes. Subsequent chapters look at quantum inspired meta-heuristics for bi-level and gray scale multi-level image thresholding; quantum behaved meta-heuristics for true color multi-level image thresholding; and quantum inspired multi-objective algorithms for gray scale multi-level image thresholding. Each chapter concludes with a summary and sample questions. Provides in-depth analysis of quantum mechanical principles Offers comprehensive review of image analysis Analyzes different state-of-the-art image thresholding approaches Detailed current, popular standard meta-heuristics in use today Guides readers step by step in the build-up of quantum inspired meta-heuristics Includes a plethora of real life case studies and applications Features statistical test analysis of the performances of the quantum inspired meta-heuristics vis-à-vis their conventional counterparts Quantum Inspired Meta-heuristics for Image Analysis is an excellent source of information for anyone working with or learning quantum inspired meta-heuristics for image analysis.



Interplay Of Artificial General Intelligence With Quantum Computing


Interplay Of Artificial General Intelligence With Quantum Computing
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Author : C. Kishor Kumar Reddy
language : en
Publisher: Springer Nature
Release Date : 2025-08-12

Interplay Of Artificial General Intelligence With Quantum Computing written by C. Kishor Kumar Reddy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-12 with Computers categories.


This book investigates the dynamic relationship between artificial general intelligence (AGI) and quantum computing. AGI refers to a form of AI capable of performing any intellectual task that a human can, while quantum computing utilizes quantum mechanics principles to process information in fundamentally different ways compared to classical computing. This interplay explores how quantum computing might enhance AGI by accelerating complex computations and optimizing learning algorithms, potentially enabling AGI systems to solve problems beyond the reach of traditional computers. It also examines the challenges and opportunities presented by combining these technologies, including theoretical implications and practical applications in advancing AI capabilities. This book examines the groundbreaking intersection of artificial general intelligence (AGI) and quantum computing. The book explores how AGI, which aims to replicate human-like cognitive abilities, can be enhanced by quantum computing's unique processing capabilities. It delves into theoretical foundations, practical applications, and potential synergies, illustrating how quantum computing could tackle complex computational challenges inherent in AGI development. By integrating these advanced technologies, the book provides a comprehensive analysis of their combined impact, offering insights into future advancements and the transformative potential of merging AGI with quantum computing.



Metaheuristic Algorithms For Image Segmentation Theory And Applications


Metaheuristic Algorithms For Image Segmentation Theory And Applications
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Author : Diego Oliva
language : en
Publisher: Springer
Release Date : 2020-08-14

Metaheuristic Algorithms For Image Segmentation Theory And Applications written by Diego Oliva and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-14 with Technology & Engineering categories.


This book presents a study of the most important methods of image segmentation and how they are extended and improved using metaheuristic algorithms. The segmentation approaches selected have been extensively applied to the task of segmentation (especially in thresholding), and have also been implemented using various metaheuristics and hybridization techniques leading to a broader understanding of how image segmentation problems can be solved from an optimization perspective. The field of image processing is constantly changing due to the extensive integration of cameras in devices; for example, smart phones and cars now have embedded cameras. The images have to be accurately analyzed, and crucial pre-processing steps, like image segmentation, and artificial intelligence, including metaheuristics, are applied in the automatic analysis of digital images. Metaheuristic algorithms have also been used in various fields of science and technology as the demand for new methods designed to solve complex optimization problems increases. This didactic book is primarily intended for undergraduate and postgraduate students of science, engineering, and computational mathematics. It is also suitable for courses such as artificial intelligence, advanced image processing, and computational intelligence. The material is also useful for researches in the fields of evolutionary computation, artificial intelligence, and image processing.



Optimization Techniques In Computer Vision


Optimization Techniques In Computer Vision
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Author : Mongi A. Abidi
language : en
Publisher: Springer
Release Date : 2016-12-06

Optimization Techniques In Computer Vision written by Mongi A. Abidi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-06 with Computers categories.


This book presents practical optimization techniques used in image processing and computer vision problems. Ill-posed problems are introduced and used as examples to show how each type of problem is related to typical image processing and computer vision problems. Unconstrained optimization gives the best solution based on numerical minimization of a single, scalar-valued objective function or cost function. Unconstrained optimization problems have been intensively studied, and many algorithms and tools have been developed to solve them. Most practical optimization problems, however, arise with a set of constraints. Typical examples of constraints include: (i) pre-specified pixel intensity range, (ii) smoothness or correlation with neighboring information, (iii) existence on a certain contour of lines or curves, and (iv) given statistical or spectral characteristics of the solution. Regularized optimization is a special method used to solve a class of constrained optimization problems. The term regularization refers to the transformation of an objective function with constraints into a different objective function, automatically reflecting constraints in the unconstrained minimization process. Because of its simplicity and efficiency, regularized optimization has many application areas, such as image restoration, image reconstruction, optical flow estimation, etc. Optimization plays a major role in a wide variety of theories for image processing and computer vision. Various optimization techniques are used at different levels for these problems, and this volume summarizes and explains these techniques as applied to image processing and computer vision.