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Spectral-Spatial Classification of Hyperspectral Remote Sensing Images
This comprehensive new resource brings you up to date on recent developments in the classification of hyperspectral images using both spectral and spatial information, including advanced statistical approaches and methods. The inclusion of spatial information to traditional approaches for hyperspectral classification has been one of the most active and relevant innovative lines of research in remote sensing during recent years. This book gives you insight into several important challenges when performing hyperspectral image classification related to the imbalance between high dimensionality and limited availability of training samples, or the presence of mixed pixels in the data. This book also shows you how to integrate spatial and spectral information in order to take advantage of the benefits that both sources of information provide.
Fractional Order Darwinian Particle Swarm Optimization
This book examines the bottom-up applicability of swarm intelligence to solving multiple problems, such as curve fitting, image segmentation, and swarm robotics. It compares the capabilities of some of the better-known bio-inspired optimization approaches, especially Particle Swarm Optimization (PSO), Darwinian Particle Swarm Optimization (DPSO) and the recently proposed Fractional Order Darwinian Particle Swarm Optimization (FODPSO), and comprehensively discusses their advantages and disadvantages. Further, it demonstrates the superiority and key advantages of using the FODPSO algorithm, such as its ability to provide an improved convergence towards a solution, while avoiding sub-optimality. This book offers a valuable resource for researchers in the fields of robotics, sports science, pattern recognition and machine learning, as well as for students of electrical engineering and computer science.
Computational Intelligence
This book provides a comprehensive exploration of computational intelligence techniques and their applications, offering valuable insights into advanced information processing, machine learning concepts, and their impact on agile manufacturing systems. Computational Intelligence presents a new concept for advanced information processing. Computational Intelligence (CI) is the principle, architecture, implementation, and growth of machine learning concepts that are physiologically and semantically inspired. Computational Intelligence methods aim to develop an approach to evaluating and creating flexible processing of human information, such as sensing, understanding, learning, recognizing, an...
Applications of Machine intelligence in Engineering
The Global Conference on Artificial Intelligence and Applications (GCAIA 2021) provides a prominent venue for researchers, engineers, entrepreneurs, and scholar students to share their research ideas in the area of AI. Academic researchers would reveal the results and conclusions of laboratory based investigations via the GCAIA 21 platform, which bridges the gap between academia, industry, and government ethics. The GCAIA 21 platform will also bring together regional and worldwide issues to explore current advancements in contemporary Computation Intelligence. This Conference Proceedings volume contains the written versions of most of the contributions presented during the conference of GCAIA 2021. The conference has provided an excellent chance for researchers from diverse locations to present and debate their work in the field of artificial intelligence and its applications. It includes a selection of 62 papers. All accepted papers were subjected to strict peer-review by 2–4 expert referees. The papers have been selected for this volume because of their quality and their relevance to the theme of the conference.
Handbook of Radar Scattering Statistics for Terrain
The classic reference for radar and remote sensing engineers, Handbook of Radar for Scattering Statistics for Terrain, has been reissued with updated, practical software for modern data analysis applications. First published in 1989, this update features a new preface, along with three new appendices that explain how to use the new software and graphical user interface. Python- and MATLAB-based software has been utilized so remote sensing and radar engineers can utilize the wealth of statistical data that came with the original book and software. This update combines the book and software, previously sold separately, into a single new product. The text first presents detailed examinations of...
Measurement Systems and Sensors, Second Edition
This thoroughly updated and expanded second edition is an authoritative resource on industrial measurement systems and sensors, with particular attention given to temperature, stress, pressure, acceleration, and liquid flow sensors. This edition includes new and expanded chapters on wireless measuring systems and measurement control and diagnostics systems in cars. Moreover, the book introduces new, cost-effective measurement technology utilizing www servers and LAN computer networks - a topic not covered in any other resource. Coverage of updated wireless measurement systems and wireless GSM/LTE interfacing make this book unique, providing in-depth, practical knowledge. Professionals learn ...
Multiple Classifier Systems
This book constitutes the refereed proceedings of the 11th International Workshop on Multiple Classifier Systems, MCS 2013, held in Nanjing, China, in May 2013. The 34 revised papers presented together with two invited papers were carefully reviewed and selected from 59 submissions. The papers address issues in multiple classifier systems and ensemble methods, including pattern recognition, machine learning, neural network, data mining and statistics.
The Role of Geospatial Technologies in Landslide Hazard Assessment
This book is designed to provide a detailed, methodological framework for landslide hazard assessment. The focus is on various dimensions of landslide hazard assessment, including the terminologies used in landslide hazard analysis and landslide inventory systems used globally and their relevance in generating a complete and reliable landslide database for further analysis, supported by global case studies. It includes an overview of the methodological developments in landslide hazard assessment and role of geospatial technologies in landslide studies. Features: Helps readers to understand the technical details of geospatial techniques applied in hazard management. Deals with the practicalit...
Methods and Applications of Autonomous Experimentation
Autonomous Experimentation is poised to revolutionize scientific experiments at advanced experimental facilities. Whereas previously, human experimenters were burdened with the laborious task of overseeing each measurement, recent advances in mathematics, machine learning and algorithms have alleviated this burden by enabling automated and intelligent decision-making, minimizing the need for human interference. Illustrating theoretical foundations and incorporating practitioners’ first-hand experiences, this book is a practical guide to successful Autonomous Experimentation. Despite the field’s growing potential, there exists numerous myths and misconceptions surrounding Autonomous Experimentation. Combining insights from theorists, machine-learning engineers and applied scientists, this book aims to lay the foundation for future research and widespread adoption within the scientific community. This book is particularly useful for members of the scientific community looking to improve their research methods but also contains additional insights for students and industry professionals interested in the future of the field.
