Positioning And Navigation Using Machine Learning Methods
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Positioning And Navigation Using Machine Learning Methods
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Author : Kegen Yu
language : en
Publisher: Springer Nature
Release Date : 2024-09-17
Positioning And Navigation Using Machine Learning Methods written by Kegen Yu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-17 with Technology & Engineering categories.
This is the first book completely dedicated to positioning and navigation using machine learning methods. It deals with ground, aerial, and space positioning and navigation for pedestrians, vehicles, UAVs, and LEO satellites. Most of the major machine learning methods are utilized, including supervised learning, unsupervised learning, deep learning, and reinforcement learning. The book presents both fundamentals and in-depth studies as well as practical examples in positioning and navigation. Extensive data processing and experimental results are provided in the major chapters through conducting experimental campaigns or using in-situ measurements.
Handbook Of Augmented And Virtual Reality
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Author : Sumit Badotra
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2023-08-21
Handbook Of Augmented And Virtual Reality written by Sumit Badotra and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-21 with Computers categories.
Augmented and Virtual Reality are revolutionizing present and future technologies: these are the fastest growing and most fascinating areas of technologies at present. This book aims to provide insight into the theory and applications of Augmented and Virtual Reality to multiple technologies such as IoT (Internet of Things), ML (Machine Learning), AI (Artifi cial Intelligence), Healthcare and Education.
Dynamic Neural Networks For Robot Systems Data Driven And Model Based Applications
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Author : Long Jin
language : en
Publisher: Frontiers Media SA
Release Date : 2024-07-24
Dynamic Neural Networks For Robot Systems Data Driven And Model Based Applications written by Long Jin and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-24 with Science categories.
Neural network control has been a research hotspot in academic fields due to the strong ability of computation. One of its wildly applied fields is robotics. In recent years, plenty of researchers have devised different types of dynamic neural network (DNN) to address complex control issues in robotics fields in reality. Redundant manipulators are no doubt indispensable devices in industrial production. There are various works on the redundancy resolution of redundant manipulators in performing a given task with the manipulator model information known. However, it becomes knotty for researchers to precisely control redundant manipulators with unknown model to complete a cyclic-motion generation CMG task, to some extent. It is worthwhile to investigate the data-driven scheme and the corresponding novel dynamic neural network (DNN), which exploits learning and control simultaneously. Therefore, it is of great significance to further research the special control features and solve challenging issues to improve control performance from several perspectives, such as accuracy, robustness, and solving speed.
Recent Advances In Big Data Machine And Deep Learning For Precision Agriculture
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Author : Muhammad Fazal Ijaz
language : en
Publisher: Frontiers Media SA
Release Date : 2024-02-19
Recent Advances In Big Data Machine And Deep Learning For Precision Agriculture written by Muhammad Fazal Ijaz and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-19 with Science categories.
Computational Science Iccs 2021
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Author : Maciej Paszynski
language : en
Publisher: Springer Nature
Release Date : 2021-06-09
Computational Science Iccs 2021 written by Maciej Paszynski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-09 with Computers categories.
The six-volume set LNCS 12742, 12743, 12744, 12745, 12746, and 12747 constitutes the proceedings of the 21st International Conference on Computational Science, ICCS 2021, held in Krakow, Poland, in June 2021.* The total of 260 full papers and 57 short papers presented in this book set were carefully reviewed and selected from 635 submissions. 48 full and 14 short papers were accepted to the main track from 156 submissions; 212 full and 43 short papers were accepted to the workshops/ thematic tracks from 479 submissions. The papers were organized in topical sections named: Part I: ICCS Main Track Part II: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Biomedical and Bioinformatics Challenges for Computer Science Part III: Classifier Learning from Difficult Data; Computational Analysis of Complex Social Systems; Computational Collective Intelligence; Computational Health Part IV: Computational Methods for Emerging Problems in (dis-)Information Analysis; Computational Methods in Smart Agriculture; Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart Systems Part V: Computer Graphics, Image Processing and Artificial Intelligence; Data-Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; MeshFree Methods and Radial Basis Functions in Computational Sciences; Multiscale Modelling and Simulation Part VI: Quantum Computing Workshop; Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Software Engineering for Computational Science; Solving Problems with Uncertainty; Teaching Computational Science; Uncertainty Quantification for Computational Models *The conference was held virtually.
Computational Artificial Intelligence And Methods For Industries
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Author : Vijayarangan Natarajan
language : en
Publisher: Springer Nature
Release Date : 2025-07-04
Computational Artificial Intelligence And Methods For Industries written by Vijayarangan Natarajan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-04 with Computers categories.
This book presents the result of an innovative challenge, to create a systematic literature overview driven by machine-generated content. Questions and related keywords were prepared for the machine to query, discover, collate and structure by Artificial Intelligence (AI) clustering. The AI-based approach seemed especially suitable to provide an innovative perspective as the topics are indeed both complex, interdisciplinary and multidisciplinary, for example, climate, planetary and evolution sciences. Springer Nature has published much on these topics in its journals over the years, so the challenge was for the machine to identify the most relevant content and present it in a structured way that the reader would find useful. The automatically generated literature summaries in this book are intended as a springboard to further discoverability. They are particularly useful to readers with limited time, looking to learn more about the subject quickly and especially if they are new to the topics. Springer Nature seeks to support anyone who needs a fast and effective start in their content discovery journey, from the undergraduate student exploring interdisciplinary content to Master- or PhD-thesis developing research questions, to the practitioner seeking support materials, this book can serve as an inspiration, to name a few examples. It is important to us as a publisher to make the advances in technology easily accessible to our authors and find new ways of AI-based author services that allow human-machine interaction to generate readable, usable, collated, research content.
Machine Learning For Indoor Localization And Navigation
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Author : Saideep Tiku
language : en
Publisher: Springer Nature
Release Date : 2023-06-29
Machine Learning For Indoor Localization And Navigation written by Saideep Tiku and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-29 with Technology & Engineering categories.
While GPS is the de-facto solution for outdoor positioning with a clear sky view, there is no prevailing technology for GPS-deprived areas, including dense city centers, urban canyons, buildings and other covered structures, and subterranean facilities such as underground mines, where GPS signals are severely attenuated or totally blocked. As an alternative to GPS for the outdoors, indoor localization using machine learning is an emerging embedded and Internet of Things (IoT) application domain that is poised to reinvent the way we navigate in various indoor environments. This book discusses advances in the applications of machine learning that enable the localization and navigation of humans, robots, and vehicles in GPS-deficient environments. The book explores key challenges in the domain, such as mobile device resource limitations, device heterogeneity, environmental uncertainties, wireless signal variations, and security vulnerabilities. Countering these challenges can improve the accuracy, reliability, predictability, and energy-efficiency of indoor localization and navigation. The book identifies severalnovel energy-efficient, real-time, and robust indoor localization techniques that utilize emerging deep machine learning and statistical techniques to address the challenges for indoor localization and navigation. In particular, the book: Provides comprehensive coverage of the application of machine learning to the domain of indoor localization; Presents techniques to adapt and optimize machine learning models for fast, energy-efficient indoor localization; Covers design and deployment of indoor localization frameworks on mobile, IoT, and embedded devices in real conditions.
Multi Technology Positioning
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Author : Jari Nurmi
language : en
Publisher: Springer
Release Date : 2017-03-28
Multi Technology Positioning written by Jari Nurmi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-28 with Technology & Engineering categories.
This book provides an overview of positioning technologies, applications and services in a format accessible to a wide variety of readers. Readers who have always wanted to understand how satellite-based positioning, wireless network positioning, inertial navigation, and their combinations work will find great value in this book. Readers will also learn about the advantages and disadvantages of different positioning methods, their limitations and challenges. Cognitive positioning, adding the brain to determine which technologies to use at device runtime, is introduced as well. Coverage also includes the use of position information for Location Based Services (LBS), as well as context-aware positioning services, designed for better user experience.
Machine Learning For Complex And Unmanned Systems
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Author : Jose Martinez-Carranza
language : en
Publisher: CRC Press
Release Date : 2024-02-21
Machine Learning For Complex And Unmanned Systems written by Jose Martinez-Carranza and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-21 with Computers categories.
This book highlights applications that include machine learning methods to enhance new developments in complex and unmanned systems. The contents are organized from the applications requiring few methods to the ones combining different methods and discussing their development and hardware/software implementation. The book includes two parts: the first one collects machine learning applications in complex systems, mainly discussing developments highlighting their modeling and simulation, and hardware implementation. The second part collects applications of machine learning in unmanned systems including optimization and case studies in submarines, drones, and robots. The chapters discuss miscellaneous applications required by both complex and unmanned systems, in the areas of artificial intelligence, cryptography, embedded hardware, electronics, the Internet of Things, and healthcare. Each chapter provides guidelines and details of different methods that can be reproduced in hardware/software and discusses future research. Features Provides details of applications using machine learning methods to solve real problems in engineering Discusses new developments in the areas of complex and unmanned systems Includes details of hardware/software implementation of machine learning methods Includes examples of applications of different machine learning methods for future lines for research in the hot topic areas of submarines, drones, robots, cryptography, electronics, healthcare, and the Internet of Things This book can be used by graduate students, industrial and academic professionals to examine real case studies in applying machine learning in the areas of modeling, simulation, and optimization of complex systems, cryptography, electronics, healthcare, control systems, Internet of Things, security, and unmanned systems such as submarines, drones, and robots.
Recent Advances In Indoor Localization Systems And Technologies
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Author : Gyula Simon
language : en
Publisher: MDPI
Release Date : 2021-08-30
Recent Advances In Indoor Localization Systems And Technologies written by Gyula Simon and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-30 with Technology & Engineering categories.
Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods.