Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing, Pasricha
Автор: Hainey, Thomas (school Of Computing, Engineering And Physical Sciences, University Of The West Of Scotland) Baxter, Gavin Название: Writing successful undergraduate dissertations in games development and computer science ISBN: 0367517086 ISBN-13(EAN): 9780367517083 Издательство: Taylor&Francis Рейтинг: Цена: 3367.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Writing a dissertation in the final year at university can be a highly daunting task for any student, but particularly if the degree is practically oriented and implementation based. This book provides an accessible, concise guide to producing a dissertation in computer science, software engineering, or games development degrees, with research projects typically involving design, implementation, testing, and evaluation.Drawing on the authors’ extensive knowledge and experience of supervising dissertation students, the book offers a step-by-step guide to the key areas of writing a dissertation alongside real-life examples. Chapters cover:Producing literature reviews.Formulating research questions.Understanding epistemologies.Selecting methodologies and research methods.Software development life cycle methodologies.Evaluation, statistical analysis, and formulating conclusions.Working methodically through the different stages of writing a dissertation, this is an essential comprehensive guide for all students producing any form of dissertation in computer science, software engineering, or games development.
Автор: Edited By Sheetal S. Zalte-Gaikwad, Indranath Chat Название: Synergistic interaction of big data with cloud computing for Industry 4.0 / ISBN: 1032245085 ISBN-13(EAN): 9781032245089 Издательство: Taylor&Francis Рейтинг: Цена: 25265.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The goal of this book is to help aspiring readers and researchers understand the convergence of Big Data with the Cloud. This book presents the latest information on the adaptation and implementation of Big Data technologies in various cloud domains and Industry 4.0.
Автор: Brunone, Federica Cucuzza, Marco Imperadori, Marco Vanossi, Andrea Название: IoT and WSN based Smart Cities: A Machine Learning Perspective ISBN: 3030841812 ISBN-13(EAN): 9783030841812 Издательство: Springer Рейтинг: Цена: 18294.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides an investigative approach to how machine learning is helping to maintain and secure smart cities, including principal uses such as smart monitoring, privacy, reliability, and public protection.
Описание: This book provides comprehensive coverage of various solutions that address issues related to real-time performance, security, and robustness in emerging automotive platforms. The authors discuss recent advances towards the goal of enabling reliable, secure, and robust, time-critical automotive cyber-physical systems, using advanced optimization and machine learning techniques. The focus is on presenting state-of-the-art solutions to various challenges including real-time data scheduling, secure communication within and outside the vehicle, tolerance to faults, optimizing the use of resource-constrained automotive ECUs, intrusion detection, and developing robust perception and control techniques for increasingly autonomous vehicles.
Автор: Easwaran Balamurugan, Hiran Kamal Kant, Krishnan Sangeetha Название: Real-Time Applications of Machine Learning in Cyber-Physical Systems ISBN: 179989309X ISBN-13(EAN): 9781799893097 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 23199.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Technological advancements of recent decades have reshaped the way people socialize, work, learn, and ultimately live. The use of cyber-physical systems (CPS) specifically have helped people lead their lives with greater control and freedom. CPS domains have great societal significance, providing crucial assistance in industries ranging from security to healthcare. At the same time, machine learning (ML) algorithms are known for being substantially efficient, high performing, and have become a real standard due to greater accessibility, and now more than ever, multidisciplinary applications of ML for CPS have become a necessity to help uncover constructive solutions for real-world problems. Real-Time Applications of Machine Learning in Cyber-Physical Systems provides a relevant theoretical framework and the most recent empirical findings on various real-time applications of machine learning in cyber-physical systems. Covering topics like intrusion detection systems, predictive maintenance, and seizure prediction, this book is an essential resource for researchers, machine learning professionals, independent researchers, scholars, scientists, libraries, and academicians.
Описание: This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. * Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; * Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; * Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.
Описание: This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits.
Автор: Shuvra S. Bhattacharyya; Miodrag Potkonjak; Senem Название: Embedded, Cyber-Physical, and IoT Systems ISBN: 3030169480 ISBN-13(EAN): 9783030169480 Издательство: Springer Рейтинг: Цена: 12196.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This Festschrift is in honor of Marilyn Wolf, on the occasion of her 60th birthday. Prof. Wolf is a renowned researcher and educator in Electrical and Computer Engineering, who has made pioneering contributions in all of the major areas in Embedded, Cyber-Physical, and Internet of Things (IoT) Systems. This book provides a timely collection of contributions that cover important topics related to Smart Cameras, Hardware/Software Co-Design, and Multimedia applications.
Embedded systems are everywhere; cyber-physical systems enable monitoring and control of complex physical processes with computers; and IoT technology is of increasing relevance in major application areas, including factory automation, and smart cities. Smart cameras and multimedia technologies introduce novel opportunities and challenges in embedded, cyber-physical and IoT applications. Advanced hardware/software co-design methodologies provide valuable concepts and tools for addressing these challenges.
The diverse topics of the chapters in this Festschrift help to reflect the great breadth and depth of Marilyn Wolf's contributions in research and education. The chapters have been written by some of Marilyn’s closest collaborators and colleagues.
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