Deep Learning For Unmanned Systems

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Deep Learning for Unmanned Systems

Author : Anis Koubaa
Publisher : Springer Nature
ISBN 13 : 3030779394
Total Pages : 731 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Deep Learning for Unmanned Systems by : Anis Koubaa

Download or read book Deep Learning for Unmanned Systems written by Anis Koubaa and published by Springer Nature. This book was released on 2021-10-01 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Intelligent Autonomous Drones with Cognitive Deep Learning

Author : David Allen Blubaugh
Publisher : Apress
ISBN 13 : 9781484268025
Total Pages : 0 pages
Book Rating : 4.2/5 (68 download)

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Book Synopsis Intelligent Autonomous Drones with Cognitive Deep Learning by : David Allen Blubaugh

Download or read book Intelligent Autonomous Drones with Cognitive Deep Learning written by David Allen Blubaugh and published by Apress. This book was released on 2022-11-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Machine Learning for Complex and Unmanned Systems

Author : Esteban Tlelo-Cuautle
Publisher :
ISBN 13 : 9781032473307
Total Pages : 0 pages
Book Rating : 4.4/5 (733 download)

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Book Synopsis Machine Learning for Complex and Unmanned Systems by : Esteban Tlelo-Cuautle

Download or read book Machine Learning for Complex and Unmanned Systems written by Esteban Tlelo-Cuautle and published by . This book was released on 2023-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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"--

Autonomous Robotics and Deep Learning

Author : Vishnu Nath
Publisher : Springer Science & Business Media
ISBN 13 : 3319056034
Total Pages : 66 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Autonomous Robotics and Deep Learning by : Vishnu Nath

Download or read book Autonomous Robotics and Deep Learning written by Vishnu Nath and published by Springer Science & Business Media. This book was released on 2014-04-11 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Springer Brief examines the combination of computer vision techniques and machine learning algorithms necessary for humanoid robots to develop “true consciousness.” It illustrates the critical first step towards reaching “deep learning,” long considered the holy grail for machine learning scientists worldwide. Using the example of the iCub, a humanoid robot which learns to solve 3D mazes, the book explores the challenges to create a robot that can perceive its own surroundings. Rather than relying solely on human programming, the robot uses physical touch to develop a neural map of its environment and learns to change the environment for its own benefit. These techniques allow the iCub to accurately solve any maze, if a solution exists, within a few iterations. With clear analysis of the iCub experiments and its results, this Springer Brief is ideal for advanced level students, researchers and professionals focused on computer vision, AI and machine learning.

Unmanned Aerial Systems

Author : Anis Koubaa
Publisher : Academic Press
ISBN 13 : 0128202777
Total Pages : 652 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Unmanned Aerial Systems by : Anis Koubaa

Download or read book Unmanned Aerial Systems written by Anis Koubaa and published by Academic Press. This book was released on 2021-01-21 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned Aerial Systems: Theoretical Foundation and Applications presents some of the latest innovative approaches to drones from the point-of-view of dynamic modeling, system analysis, optimization, control, communications, 3D-mapping, search and rescue, surveillance, farmland and construction monitoring, and more. With the emergence of low-cost UAS, a vast array of research works in academia and products in the industrial sectors have evolved. The book covers the safe operation of UAS, including, but not limited to, fundamental design, mission and path planning, control theory, computer vision, artificial intelligence, applications requirements, and more. This book provides a unique reference of the state-of-the-art research and development of unmanned aerial systems, making it an essential resource for researchers, instructors and practitioners. Covers some of the most innovative approaches to drones Provides the latest state-of-the-art research and development surrounding unmanned aerial systems Presents a comprehensive reference on unmanned aerial systems, with a focus on cutting-edge technologies and recent research trends in the area

Applications of Machine Learning in UAV Networks

Author : Hassan, Jahan
Publisher : IGI Global
ISBN 13 :
Total Pages : 425 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Applications of Machine Learning in UAV Networks by : Hassan, Jahan

Download or read book Applications of Machine Learning in UAV Networks written by Hassan, Jahan and published by IGI Global. This book was released on 2024-01-17 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications of Machine Learning in UAV Networks presents a pioneering exploration into the symbiotic relationship between machine learning techniques and UAVs. In an age where UAVs are revolutionizing sectors as diverse as agriculture, environmental preservation, security, and disaster response, this meticulously crafted volume offers an analysis of the manifold ways machine learning drives advancements in UAV network efficiency and efficacy. This book navigates through an expansive array of domains, each demarcating a pivotal application of machine learning in UAV networks. From the precision realm of agriculture and its dynamic role in yield prediction to the ecological sensitivity of biodiversity monitoring and habitat restoration, the contours of each domain are vividly etched. These explorations are not limited to the terrestrial sphere; rather, they extend to the pivotal aerial missions of wildlife conservation, forest fire monitoring, and security enhancement, where UAVs adorned with machine learning algorithms wield an instrumental role. Scholars and practitioners from fields as diverse as machine learning, UAV technology, robotics, and IoT networks will find themselves immersed in a confluence of interdisciplinary expertise. The book's pages cater equally to professionals entrenched in agriculture, environmental studies, disaster management, and beyond.

Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems

Author : Uddin, M. Irfan
Publisher : IGI Global
ISBN 13 :
Total Pages : 307 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems by : Uddin, M. Irfan

Download or read book Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems written by Uddin, M. Irfan and published by IGI Global. This book was released on 2024-02-26 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: The applications of rapidly advancing intelligent systems are so varied that many are still yet to be discovered. There is often a disconnect between experts in computer science, artificial intelligence, machine learning, robotics, and other specialties, which inhibits the potential for the expansion of this technology and its many benefits. A resource that encourages interdisciplinary collaboration is needed to bridge the gap between these respected leaders of their own fields. Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems represents an exploration of the forefront of artificial intelligence, navigating the complexities of this field and its many applications. This guide expertly navigates through the intricate domains of deep learning and reinforcement learning, offering an in-depth journey through foundational principles, advanced methodologies, and cutting-edge algorithms shaping the trajectory of intelligent systems. The book covers an introduction to artificial intelligence and its subfields, foundational aspects of deep learning, a demystification of the architecture of neural networks, the mechanics of backpropagation, and the intricacies of critical elements such as activation and loss functions. The book serves as a valuable educational resource for professionals. Its structured approach makes it an ideal reference for students, researchers, and industry professionals.

Applications of Machine Learning

Author : Prashant Johri
Publisher : Springer Nature
ISBN 13 : 9811533571
Total Pages : 404 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Applications of Machine Learning by : Prashant Johri

Download or read book Applications of Machine Learning written by Prashant Johri and published by Springer Nature. This book was released on 2020-05-04 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 for Robotics and Autonomous Systems Applications

Author : Ahmad Taher Azar
Publisher : Springer Nature
ISBN 13 : 3031287150
Total Pages : 488 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Artificial Intelligence for Robotics and Autonomous Systems Applications by : Ahmad Taher Azar

Download or read book Artificial Intelligence for Robotics and Autonomous Systems Applications written by Ahmad Taher Azar and published by Springer Nature. This book was released on 2023-05-15 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques

Author : Thusnavis, Bella Mary I.
Publisher : IGI Global
ISBN 13 : 1799887650
Total Pages : 325 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques by : Thusnavis, Bella Mary I.

Download or read book Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques written by Thusnavis, Bella Mary I. and published by IGI Global. This book was released on 2022-05-27 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned aerial vehicles (UAVs) and artificial intelligence (AI) are gaining the attention of academic and industrial researchers due to the freedoms that UAVs afford when operating and monitoring activities remotely. Applying machine learning and deep learning techniques can result in fast and reliable outputs and have helped in real-time monitoring, data collection and processing, and prediction. UAVs utilizing these techniques can become instrumental tools for computer/wireless networks, smart cities, military applications, agricultural sectors, and mining. Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques is an essential reference source that covers pattern recognition, machine and deep learning-based methods, and other AI techniques and the impact they have when applied to different real-time applications of UAVs. It synthesizes the scope and importance of machine learning and deep learning models in enhancing UAV capabilities, solutions to problems, and numerous application areas. Covering topics such as vehicular surveillance systems, yield prediction, and human activity recognition, this premier reference source is a comprehensive resource for computer scientists; AI engineers; data scientists; agriculturalists; government officials; military leaders; business managers and leaders; students and faculty of higher education; academic libraries; academicians; and researchers in computer science, computer vision, pattern recognition, imaging, and engineering.

Designing Autonomous AI

Author : Kence Anderson
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098110722
Total Pages : 248 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Designing Autonomous AI by : Kence Anderson

Download or read book Designing Autonomous AI written by Kence Anderson and published by "O'Reilly Media, Inc.". This book was released on 2022-06-22 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world. Using concrete examples, minimal theory, and a proven architectural framework, author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns, as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students, process operators, data scientists, machine learning algorithm experts, and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI. This book examines: Differences between and limitations of automated, autonomous, and human decision-making Unique advantages of autonomous AI for real-time decision-making, with use cases How to design an autonomous AI from modular components and document your designs

Intelligent Unmanned Systems: Theory and Applications

Author : Agus Budiyono
Publisher : Springer Science & Business Media
ISBN 13 : 3642002633
Total Pages : 279 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Intelligent Unmanned Systems: Theory and Applications by : Agus Budiyono

Download or read book Intelligent Unmanned Systems: Theory and Applications written by Agus Budiyono and published by Springer Science & Business Media. This book was released on 2009-03-20 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book largely represents the extended version of select papers from the Inter- tional Conference on Intelligent Unmanned System ICIUS 2007 which was jointly organized by the Center for Unmanned System Studies at Institut Teknologi Bandung, Artificial Muscle Research Center at Konkuk University and Institute of Bio-inspired Structure and Surface Engineering, Nanjing University of Aeronautics and Astrona- ics. The joint-event was the 3rd conference extending from International Conference on Emerging System Technology (ICEST) in 2005 and International Conference on Technology Fusion (ICTF) in 2006 both conducted in Seoul. ICIUS 2007 was focused on both theory and application primarily covering the topics on robotics, autonomous vehicles and intelligent unmanned technologies. The conference was arranged into three parallel symposia with the following scope of topics: Unmanned Systems: Micro air vehicle, Underwater vehicle, Micro-satellite, - manned aerial vehicle, Multi-agent systems, Autonomous ground vehicle, Blimp, Swarm intelligence, learning and control Robotics and Biomimetics: Artificial muscle actuators, Smart sensors, Design and applications of MEMS/NEMS system, Intelligent robot system, Evolutionary al- rithm, Control of biological systems, AI and expert systems, Biological learning control systems, Neural networks, Genetic algorithm Control and Intelligent System: Distributed intelligence, Distributed/decentralized intelligent control, Distributed or decentralized control methods, Distributed and - bedded systems, Embedded intelligent control, Complex systems, Discrete event s- tems, Hybrid systems, Networked control systems, Delay systems, Fuzzy systems, Identification and estimation, Nonlinear systems, Precision motion control, Control applications, Control engineering education.

Handbook of Research on Machine and Deep Learning Applications for Cyber Security

Author : Ganapathi, Padmavathi
Publisher : IGI Global
ISBN 13 : 1522596135
Total Pages : 482 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Handbook of Research on Machine and Deep Learning Applications for Cyber Security by : Ganapathi, Padmavathi

Download or read book Handbook of Research on Machine and Deep Learning Applications for Cyber Security written by Ganapathi, Padmavathi and published by IGI Global. This book was released on 2019-07-26 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the advancement of technology continues, cyber security continues to play a significant role in todays world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security. The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.

Unmanned Aircraft Systems

Author : Ella Atkins
Publisher : John Wiley & Sons
ISBN 13 : 1118866452
Total Pages : 740 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Unmanned Aircraft Systems by : Ella Atkins

Download or read book Unmanned Aircraft Systems written by Ella Atkins and published by John Wiley & Sons. This book was released on 2017-01-17 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: UNMANNED AIRCRAF T SYSTEMS UNMANNED AIRCRAF T SYSTEMS An unmanned aircraft system (UAS), sometimes called a drone, is an aircraft without a human pilot on board ??? instead, the UAS can be controlled by an operator station on the ground or may be autonomous in operation. UAS are capable of addressing a broad range of applications in diverse, complex environments. Traditionally employed in mainly military applications, recent regulatory changes around the world are leading to an explosion of interest and wide-ranging new applications for UAS in civil airspace. Covering the design, development, operation, and mission profiles of unmanned aircraft systems, this single, comprehensive volume forms a complete, stand-alone reference on the topic. The volume integrates with the online Wiley Encyclopedia of Aerospace Engineering, providing many new and updated articles for existing subscribers to that work. The chapters cover the following items: Airframe configurations and design (launch systems, power generation, propulsion) Operations (missions, integration issues, and airspace access) Coordination (multivehicle cooperation and human oversight) With contributions from leading experts, this volume is intended to be a valuable addition, and a useful resource, for aerospace manufacturers and suppliers, governmental and industrial aerospace research establishments, airline and aviation industries, university engineering and science departments, and industry analysts, consultants, and researchers.

Unmanned Aerial Vehicles Applications: Challenges and Trends

Author : Mohamed Abdelkader
Publisher : Springer Nature
ISBN 13 : 3031320379
Total Pages : 404 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Unmanned Aerial Vehicles Applications: Challenges and Trends by : Mohamed Abdelkader

Download or read book Unmanned Aerial Vehicles Applications: Challenges and Trends written by Mohamed Abdelkader and published by Springer Nature. This book was released on 2023-06-29 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a book that covers different aspects of UAV technology, including design and development, applications, security and communication, and legal and regulatory challenges. The book is divided into 13 chapters, grouped into four parts. The first part discusses the design and development of UAVs, including ROS customization, structured designs, and intelligent trajectory tracking. The second part explores diverse applications such as search and rescue, monitoring distributed parameter systems, and leveraging drone technology in accounting. The third part focuses on security and communication challenges, including security concerns, multi-UAV systems, and communications security. The final part delves into the legal and regulatory challenges of integrating UAVs into non-segregated airspace. The book serves as a valuable resource for researchers, practitioners, and students in the field of unmanned aerial vehicles, providing a comprehensive understanding of UAV technology and its applications.

Engineering Applications of Neural Networks

Author : John Macintyre
Publisher : Springer
ISBN 13 : 3030202577
Total Pages : 546 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Engineering Applications of Neural Networks by : John Macintyre

Download or read book Engineering Applications of Neural Networks written by John Macintyre and published by Springer. This book was released on 2019-05-14 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th International Conference on Engineering Applications of Neural Networks, EANN 2019, held in Xersonisos, Crete, Greece, in May 2019. The 35 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 72 submissions. The papers are organized in topical sections on AI in energy management - industrial applications; biomedical - bioinformatics modeling; classification - learning; deep learning; deep learning - convolutional ANN; fuzzy - vulnerability - navigation modeling; machine learning modeling - optimization; ML - DL financial modeling; security - anomaly detection; 1st PEINT workshop.

Intelligent Autonomous Systems 15

Author : Marcus Strand
Publisher : Springer
ISBN 13 : 3030013707
Total Pages : 985 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Intelligent Autonomous Systems 15 by : Marcus Strand

Download or read book Intelligent Autonomous Systems 15 written by Marcus Strand and published by Springer. This book was released on 2018-12-31 with total page 985 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest advances and research achievements in the fields of autonomous robots and intelligent systems, presented at the IAS-15 conference, held in Baden-Baden, Germany, in June 2018. It brings together contributions from researchers, engineers and practitioners from all over the world on the main trends of robotics: navigation, path planning, robot vision, human detection, and robot design – as well as a wide range of applications. This installment of the conference reflects the rise of machine learning and deep learning in the robotics field, as employed in a variety of applications and systems. All contributions were selected using a rigorous peer-review process to ensure their scientific quality. The series of biennial IAS conferences was started in 1986: since then, it has become an essential venue for the robotics community.