Machine Learning For Complex And Unmanned Systems
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Machine Learning For Complex And Unmanned Systems
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Author : Esteban Tlelo-Cuautle
language : en
Publisher:
Release Date : 2023-12
Machine Learning For Complex And Unmanned Systems written by Esteban Tlelo-Cuautle and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12 with Technology & Engineering categories.
"This book highlights applications that include machine learning methods to enhance new developments in complex and unmanned systems. The main topics covered under this title include: machine learning, artificial intelligence, cryptography, submarines, drones, security in healthcare, Internet of Things and robotics. This book can be used by graduate students, industrial and academic professionals to revise 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"--
Deep Learning For Unmanned Systems
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Author : Anis Koubaa
language : en
Publisher: Springer Nature
Release Date : 2021-10-01
Deep Learning For Unmanned Systems written by Anis Koubaa and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-01 with Technology & Engineering categories.
This book is used at the graduate or advanced undergraduate level and many others. Manned and unmanned ground, aerial and marine vehicles enable many promising and revolutionary civilian and military applications that will change our life in the near future. These applications include, but are not limited to, surveillance, search and rescue, environment monitoring, infrastructure monitoring, self-driving cars, contactless last-mile delivery vehicles, autonomous ships, precision agriculture and transmission line inspection to name just a few. These vehicles will benefit from advances of deep learning as a subfield of machine learning able to endow these vehicles with different capability such as perception, situation awareness, planning and intelligent control. Deep learning models also have the ability to generate actionable insights into the complex structures of large data sets. In recent years, deep learning research has received an increasing amount of attention from researchers in academia, government laboratories and industry. These research activities have borne some fruit in tackling some of the challenging problems of manned and unmanned ground, aerial and marine vehicles that are still open. Moreover, deep learning methods have been recently actively developed in other areas of machine learning, including reinforcement training and transfer/meta-learning, whereas standard, deep learning methods such as recent neural network (RNN) and coevolutionary neural networks (CNN). The book is primarily meant for researchers from academia and industry, who are working on in the research areas such as engineering, control engineering, robotics, mechatronics, biomedical engineering, mechanical engineering and computer science. The book chapters deal with the recent research problems in the areas of reinforcement learning-based control of UAVs and deep learning for unmanned aerial systems (UAS) The book chapters present various techniques of deep learning for robotic applications. The book chapters contain a good literature survey with a long list of references. The book chapters are well written with a good exposition of the research problem, methodology, block diagrams and mathematical techniques. The book chapters are lucidly illustrated with numerical examples and simulations. The book chapters discuss details of applications and future research areas.
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.
Intelligent Autonomous Drones With Cognitive Deep Learning
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Author : David Allen Blubaugh
language : en
Publisher: Apress
Release Date : 2022-11-01
Intelligent Autonomous Drones With Cognitive Deep Learning written by David Allen Blubaugh and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-01 with Computers categories.
What is an artificial intelligence (AI)-enabled drone and what can it do? Are AI-enabled drones better than human-controlled drones? This book will answer these questions and more, and empower you to develop your own AI-enabled drone. You'll progress from a list of specifications and requirements, in small and iterative steps, which will then lead to the development of Unified Modeling Language (UML) diagrams based in part to the standards established by for the Robotic Operating System (ROS). The ROS architecture has been used to develop land-based drones. This will serve as a reference model for the software architecture of unmanned systems. Using this approach you'll be able to develop a fully autonomous drone that incorporates object-oriented design and cognitive deep learning systems that adapts to multiple simulation environments. These multiple simulation environments will also allow you to further build public trust in the safety of artificial intelligence within drones and small UAS. Ultimately, you'll be able to build a complex system using the standards developed, and create other intelligent systems of similar complexity and capability. Intelligent Autonomous Drones with Cognitive Deep Learning uniquely addresses both deep learning and cognitive deep learning for developing near autonomous drones. What You’ll Learn Examine the necessary specifications and requirements for AI enabled drones for near-real time and near fully autonomous drones Look at software and hardware requirements Understand unified modeling language (UML) and real-time UML for design Study deep learning neural networks for pattern recognition Review geo-spatial Information for the development of detailed mission planning within these hostile environments Who This Book Is For Primarily for engineers, computer science graduate students, or even a skilled hobbyist. The target readers have the willingness to learn and extend the topic of intelligent autonomous drones. They should have a willingness to explore exciting engineering projects that are limited only by their imagination. As far as the technical requirements are concerned, they must have an intermediate understanding of object-oriented programming and design.
Artificial Intelligence For Robotics And Autonomous Systems Applications
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Author : Ahmad Taher Azar
language : en
Publisher: Springer Nature
Release Date : 2023-05-15
Artificial Intelligence For Robotics And Autonomous Systems Applications written by Ahmad Taher Azar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-15 with Technology & Engineering categories.
This book addresses many applications of artificial intelligence in robotics, namely AI using visual and motional input. Robotic technology has made significant contributions to daily living, industrial uses, and medicinal applications. Machine learning, in particular, is critical for intelligent robots or unmanned/autonomous systems such as UAVs, UGVs, UUVs, cooperative robots, and so on. Humans are distinguished from animals by capacities such as receiving visual information, adjusting to uncertain circumstances, and making decisions to take action in a complex system. Significant progress has been made in robotics toward human-like intelligence; yet, there are still numerous unresolved issues. Deep learning, reinforcement learning, real-time learning, swarm intelligence, and other developing approaches such as tiny-ML have been developed in recent decades and used in robotics. Artificial intelligence is being integrated into robots in order to develop advanced robotics capable of performing multiple tasks and learning new things with a better perception of the environment, allowing robots to perform critical tasks with human-like vision to detect or recognize various objects. Intelligent robots have been successfully constructed using machine learning and deep learning AI technology. Robotics performance is improving as higher quality, and more precise machine learning processes are used to train computer vision models to recognize different things and carry out operations correctly with the desired outcome. We believe that the increasing demands and challenges offered by real-world robotic applications encourage academic research in both artificial intelligence and robotics. The goal of this book is to bring together scientists, specialists, and engineers from around the world to present and share their most recent research findings and new ideas on artificial intelligence in robotics.
Applications Of Machine Learning
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Author : Prashant Johri
language : en
Publisher: Springer Nature
Release Date : 2020-05-04
Applications Of Machine Learning written by Prashant Johri and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-04 with Technology & Engineering categories.
This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.
Artificial Intelligence Machine Learning And Blockchain In Quantum Satellite Drone And Network
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Author : Thiruselvan Subramanian
language : en
Publisher: CRC Press
Release Date : 2022-10-14
Artificial Intelligence Machine Learning And Blockchain In Quantum Satellite Drone And Network written by Thiruselvan Subramanian and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-14 with Technology & Engineering categories.
Quantum computing is a field in which advanced technologies like quantum communication, artificial intelligence and machine learning can be used to secure and speed up connectivity using quantum computers, quantum drones or quantum satellites. This book serve as a foundation for researchers and scientists in this field. Future technologies, such as quantum drone delivery systems, quicker internet and climate change mitigation, will need quantum information processing and quantum computation. This book deeply explores the importance of quantum computing in real-time applications. It may be used as a reference book for students in higher education, including undergraduate and graduate students, as well as researchers. Key features: Provides a clear insight into the Internet of Drones for academicians, postdoc fellows, research scholars, graduate and postgraduate students, industry fellows and software engineers Useful to professionals who seek information about the Internet of Drones, including experts in quantum computing and physics and post-quantum cryptography, as well as data scientists and data analysts Covers quantum computing and security for Unmanned Aerial Vehicles (UAV) or drones which are widely useful for applications such as military, government, and non-government systems Explores futuristic aspects of the Intenet of Drones to improve everyday living for ordinary people
Mastering Machine Learning A Comprehensive Guide To Success
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Author : Rick Spair
language : en
Publisher: Rick Spair
Release Date :
Mastering Machine Learning A Comprehensive Guide To Success written by Rick Spair and has been published by Rick Spair this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Welcome to "Mastering Machine Learning: A Comprehensive Guide to Success." In this book, we embark on an exciting journey into the world of machine learning (ML), exploring its concepts, techniques, and practical applications. Whether you are a beginner taking your first steps into the field or an experienced practitioner seeking to deepen your knowledge, this comprehensive guide will equip you with the tools, strategies, and insights needed to succeed in the ever-evolving landscape of ML. Machine learning is a rapidly advancing field that has revolutionized industries and transformed the way we tackle complex problems. From personalized recommendations and speech recognition systems to autonomous vehicles and medical diagnostics, machine learning has become an integral part of our daily lives. Its ability to analyze vast amounts of data, identify patterns, and make predictions has paved the way for groundbreaking advancements across various domains. However, mastering machine learning requires more than just understanding the algorithms and techniques. It requires a holistic approach that encompasses data collection and preparation, exploratory data analysis, model building, evaluation, deployment, and continuous learning. It also demands a deep understanding of the ethical and social implications of machine learning, ensuring responsible and fair use of this powerful technology. In this book, we have carefully crafted 20 comprehensive chapters that cover a wide range of topics, from the fundamentals of machine learning to advanced techniques and future trends. Each chapter provides a deep dive into a specific aspect of machine learning, offering tips, recommendations, and strategies for success. You will learn about various algorithms, data preprocessing techniques, model evaluation methods, interpretability approaches, and much more. Throughout the book, we emphasize a practical approach to machine learning. Real-world examples, case studies, and hands-on exercises are incorporated to help you gain a deeper understanding of the concepts and apply them to your own projects. We believe that active learning and practical experience are crucial for mastering machine learning, and we encourage you to explore, experiment, and build your own models. While this book serves as a comprehensive guide, it is important to note that machine learning is a rapidly evolving field. New algorithms, techniques, and technologies are constantly emerging, and staying up-to-date with the latest advancements is essential. However, the principles and foundations discussed in this book will provide you with a solid framework to adapt and navigate the ever-changing landscape of machine learning. Whether you are an aspiring data scientist, a software engineer, a researcher, or a business professional, this book is designed to be your trusted companion in your journey to mastering machine learning. By the time you reach the end, you will have gained a deep understanding of the fundamental concepts, acquired practical skills for applying machine learning in real-world scenarios, and developed the mindset needed to tackle complex challenges and drive innovation. Get ready to embark on an exciting adventure into the world of machine learning. Let's begin our journey towards mastering machine learning and unlocking its full potential. Happy learning!
Control Of Complex Systems
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Author : Kyriakos Vamvoudakis
language : en
Publisher: Butterworth-Heinemann
Release Date : 2016-07-27
Control Of Complex Systems written by Kyriakos Vamvoudakis and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-27 with Technology & Engineering categories.
In the era of cyber-physical systems, the area of control of complex systems has grown to be one of the hardest in terms of algorithmic design techniques and analytical tools. The 23 chapters, written by international specialists in the field, cover a variety of interests within the broader field of learning, adaptation, optimization and networked control. The editors have grouped these into the following 5 sections: “Introduction and Background on Control Theory”, “Adaptive Control and Neuroscience”, “Adaptive Learning Algorithms”, “Cyber-Physical Systems and Cooperative Control”, “Applications”.The diversity of the research presented gives the reader a unique opportunity to explore a comprehensive overview of a field of great interest to control and system theorists. This book is intended for researchers and control engineers in machine learning, adaptive control, optimization and automatic control systems, including Electrical Engineers, Computer Science Engineers, Mechanical Engineers, Aerospace/Automotive Engineers, and Industrial Engineers. It could be used as a text or reference for advanced courses in complex control systems. • Collection of chapters from several well-known professors and researchers that will showcase their recent work • Presents different state-of-the-art control approaches and theory for complex systems • Gives algorithms that take into consideration the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals and malicious attacks compromising the security of networked teams • Real system examples and figures throughout, make ideas concrete Includes chapters from several well-known professors and researchers that showcases their recent work Presents different state-of-the-art control approaches and theory for complex systems Explores the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals, and malicious attacks compromising the security of networked teams Serves as a helpful reference for researchers and control engineers working with machine learning, adaptive control, and automatic control systems
Modelling And Simulation For Autonomous Systems
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Author : Jan Hodicky
language : en
Publisher: Springer
Release Date : 2015-08-20
Modelling And Simulation For Autonomous Systems written by Jan Hodicky and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-20 with Computers categories.
This book constitutes the thoroughly refereed post-workshop proceedings of the First International Workshop on Modelling and Simulation for Autonomous Systems, MESAS 2014, held in Rome, Italy, in May 2014. The 32 revised full papers included in the volume were carefully reviewed and selected from 50 submissions, of which 46 were presented at the workshop. They are organized in the following topical sections: unmanned aerial vehicle, distributed simulation, robot system, military application, validation, human-machine communication, gazebo simulator, and algorithm.