Computer Vision and Machine Intelligence Paradigms for SDGs, Kannan
Автор: Aboul Ella Hassanien Название: Machine Learning Paradigms: Theory and Application ISBN: 3030023567 ISBN-13(EAN): 9783030023560 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
The book focuses on machine learning. Divided into three parts, the first part discusses the feature selection problem. The second part then describes the application of machine learning in the classification problem, while the third part presents an overview of real-world applications of swarm-based optimization algorithms.
The concept of machine learning (ML) is not new in the field of computing. However, due to the ever-changing nature of requirements in today’s world it has emerged in the form of completely new avatars. Now everyone is talking about ML-based solution strategies for a given problem set. The book includes research articles and expository papers on the theory and algorithms of machine learning and bio-inspiring optimization, as well as papers on numerical experiments and real-world applications.
Автор: Gandhi, Tapan K. Название: Advanced Machine Vision Paradigms For Medical Image Analysis ISBN: 012819295X ISBN-13(EAN): 9780128192955 Издательство: Elsevier Science Рейтинг: Цена: 132500.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to unstructured nature of medical imaging data and the volume of data produced during routine clinical process, the applicability of these meta-heuristic algorithms remains to be investigated.
Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision can exploit texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for both medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to the already high medical costs.
Автор: Pablo Duboue Название: The Art of Feature Engineering: Essentials for Machine Learning ISBN: 1108709389 ISBN-13(EAN): 9781108709385 Издательство: Cambridge Academ Рейтинг: Цена: 46470.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This is a guide for data scientists who want to use feature engineering to improve the performance of their machine learning solutions. The book provides a unified view of the field, beginning with basic concepts and techniques, followed by a cross-domain approach to advanced topics, like texts and images, with hands-on case studies.
Автор: Julio C. Rodriguez-Quinonez, Oleg Sergiyenko, Wendy Flores-Fuentes Название: Examining Optoelectronics in Machine Vision and Applications in Industry 4.0 ISBN: 1799865231 ISBN-13(EAN): 9781799865230 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 175560.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Focuses on the examination of emerging technologies for the design, fabrication, and implementation of optoelectronic sensors, devices, and systems in a machine vision approach to support industrial, commercial, and scientific applications.
Автор: Ramgopal Kashyap, A.V. Senthil Kumar Название: Challenges and Applications for Implementing Machine Learning in Computer Vision ISBN: 1799801837 ISBN-13(EAN): 9781799801832 Издательство: Mare Nostrum (Eurospan) Цена: 173190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques.
Автор: Tsihrintzis Название: Machine Learning Paradigms ISBN: 3319940295 ISBN-13(EAN): 9783319940298 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Data Analytics in the Medical, Biological and Signal Sciences.- Recommender System of Medical Reports Leveraging Cognitive Computing and Frame Semantics.- Classification Methods in Image Analysis with a Special Focus on Medical Analytics.- Medical Data Mining for Heart Diseases and the Future of Sequential Mining in Medical Field.- Machine Learning Methods for the Protein Fold Recognition Problem.
Автор: Aristomenis S. Lampropoulos; George A. Tsihrintzis Название: Machine Learning Paradigms ISBN: 3319191349 ISBN-13(EAN): 9783319191348 Издательство: Springer Рейтинг: Цена: 104480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes.
Автор: Jyotsna Kumar Mandal; Somnath Mukhopadhyay; Parama Название: Algorithms in Machine Learning Paradigms ISBN: 9811510407 ISBN-13(EAN): 9789811510403 Издательство: Springer Рейтинг: Цена: 167700.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Chapter 1. Development of Trapezoidal Hesitant-Intuitionistic Fuzzy Prioritized Operators based on Einstein Operations with their Application to Multi-Criteria Group Decision Making.- Chapter 2. Graph-based Information-Theoretic Approach for Unsupervised Feature Selection.- Chapter 3. Fact based Expert System for supplier selection with ERP data.- Chapter 4. Handling Seasonal Pattern and Prediction using Fuzzy Time Series Model.- Chapter 5. Automatic Classification of Fruits and Vegetables: A Texture-based Approach.- Chapter 6. Deep Learning based Early Sign Detection Model for Proliferative Diabetic Retinopathy in Neovascularization at the Disc.- Chapter 7. A Linear Regression Based Resource Utilization Prediction Policy For Live Migration in Cloud Computing.- Chapter 8. Tracking changing human emotions from facial image sequence by landmark triangulation: A incircle-circumcircle duo approach.- Chapter 9. Recognizing Human Emotions from Facial Images by Landmark Triangulation: A Combined Circumcenter-Incenter-Centroid Trio Feature Based Method.- Chapter 10. Stable neighbor nodes prediction with multivariate analysis in mobile ad hoc network using RNN model.- Chapter 11. A New Approach for Optimizing Initial Parameters of Lorenz Attractor and its application in PRNG.
Автор: Rajshree Srivastava, Pradeep Kumar Mallick, Siddha Название: Computational Intelligence for Machine Learning and Healthcare Informatics ISBN: 3110647826 ISBN-13(EAN): 9783110647822 Издательство: Walter de Gruyter Цена: 136310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.
Автор: Rik Das, Siddhartha Bhattacharyya, Sudarshan Nandy Название: Machine Learning Applications: Emerging Trends ISBN: 3110608537 ISBN-13(EAN): 9783110608533 Издательство: Walter de Gruyter Цена: 123910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice.
Автор: Kumar Singh Название: Machine Vision and Augmented Intelligence ISBN: 981990188X ISBN-13(EAN): 9789819901883 Издательство: Springer Рейтинг: Цена: 204970.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book comprises the proceedings of the International Conference on Machine Vision and Augmented Intelligence (MAI 2022). The conference proceedings encapsulate the best deliberations held during the conference. The diversity of participants in the event from academia, industry, and research reflects in the articles appearing in the book. The book encompasses all industrial and non-industrial applications. This book covers a wide range of topics such as modeling of disease transformation, epidemic forecast, image processing, and computer vision, augmented intelligence, soft computing, deep learning, image reconstruction, artificial intelligence in health care, brain-computer interface, cybersecurity, social network analysis, and natural language processing.
This updated compendium provides a methodical introduction with a coherent and unified repository of ensemble methods, theories, trends, challenges, and applications. More than a third of this edition comprised of new materials, highlighting descriptions of the classic methods, and extensions and novel approaches that have recently been introduced.
Along with algorithmic descriptions of each method, the settings in which each method is applicable and the consequences and tradeoffs incurred by using the method is succinctly featured. R code for implementation of the algorithm is also emphasized.
The unique volume provides researchers, students and practitioners in industry with a comprehensive, concise and convenient resource on ensemble learning methods.
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