Handbook of Research on the Impact of Deep Learning and IoT on Multi-Industry Applications, Albena Dimitrova Mihovska, Roshani Raut
Автор: Bhattacharyya Siddhartha, Banerjee Pinaki, Majumdar Dipankar Название: Handbook of Research on Advanced Hybrid Intelligent Techniques and Applications ISBN: 1466694742 ISBN-13(EAN): 9781466694743 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 41580.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Conventional computational methods, and even the latest soft computing paradigms, often fall short in their ability to offer solutions to many real-world problems due to uncertainty, imprecision, and circumstantial data. Hybrid intelligent computing is a paradigm that addresses these issues to a considerable extent.The Handbook of Research on Advanced Research on Hybrid Intelligent Techniques and Applications highlights the latest research on various issues relating to the hybridization of artificial intelligence, practical applications, and best methods for implementation. Focusing on key interdisciplinary computational intelligence research dealing with soft computing techniques, pattern mining, data analysis, and computer vision, this book is relevant to the research needs of academics, IT specialists, and graduate-level students.
Описание: Examines emergent research in handling real-world problems through the application of various computation technologies and techniques. Featuring theoretical concepts and best practices in the areas of computational intelligence, artificial intelligence, big data, and bio-inspired computing, this publication is a reference source for graduate students, professionals, academics, and researchers.
Описание: Provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, the book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science.
Автор: Aboul Ella Hassanien, Ashraf Darwish, Chiranji Lal Chowdhary Название: Handbook of Research on Deep Learning Innovations and Trends ISBN: 1522578625 ISBN-13(EAN): 9781522578628 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 43105.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Leading technology firms and research institutions are continuously exploring new techniques in artificial intelligence and machine learning. As such, deep learning has now been recognized in various real-world applications such as computer vision, image processing, biometrics, pattern recognition, and medical imaging. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient. The Handbook of Research on Deep Learning Innovations and Trends is an essential scholarly resource that presents current trends and the latest research on deep learning and explores the concepts, algorithms, and techniques of data mining and analysis. Highlighting topics such as computer vision, encryption systems, and biometrics, this book is ideal for researchers, practitioners, industry professionals, students, and academicians.
Описание: Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings.
Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers' points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.
Описание: As the advancement of technology continues, cyber security continues to play a significant role in today's 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.
Showcases the latest trends in new virtual/augmented reality healthcare and medical applications and provides an overview of the economic, psychological, educational and organizational impacts of these new applications and how we work, teach, learn and provide care.
With the current advances in technology innovation, the field of medicine and healthcare is rapidly expanding and, as a result, many different areas of human health diagnostics, treatment and care are emerging. Wireless technology is getting faster and 5G mobile technology allows the Internet of Medical Things (IoMT) to greatly improve patient care and more effectively prevent illness from developing.
This book provides an overview and review of the current and anticipated changes in medicine and healthcare due to new technologies and faster communication between users and devices.
The groundbreaking book presents state-of-the-art chapters on many subjects including:
A review of the implications of Virtual Reality (VR) and Augmented Reality (AR) healthcare applications
A review of current augmenting dental care
An overview of typical human-computer interaction (HCI) that can help inform the development of user interface designs and novel ways to evaluate human behavior to responses in VR and other new technologies
A review of telemedicine technologies
Building empathy in young children using augmented reality
AI technologies for mobile health of stroke monitoring & rehabilitation robotics control
Mobile doctor brain AI App
An artificial intelligence mobile cloud computing tool
Development of a robotic teaching aid for disabled children
Training system design of lower limb rehabilitation robot based on virtual reality
Описание: Presents research on artificial intelligence applications within the context of international business. Highlighting a wide range of topics such as diversification, risk management, and artificial intelligence, this book is ideal for marketers, business professionals, academics, practitioners, researchers, and students.
Описание: Artificial intelligence is at the forefront of research and implementation in many industries including healthcare and agriculture. Whether it's detecting disease or generating algorithms, deep learning techniques are advancing exponentially. Researchers and professionals need a platform in which they can keep up with machine learning trends and their developments in the real world.
The Handbook of Research on Applications and Implementations of Machine Learning Techniques provides innovative insights into the multi-disciplinary applications of machine learning algorithms for data analytics. The content within this publication examines disease identification, neural networks, and language support. It is designed for IT professionals, developers, data analysts, technology specialists, R&D professionals, industrialists, practitioners, researchers, academicians, and students seeking research on deep learning procedures and their enactments in the fields of medicine, engineering, and computer science.
Описание: Decades of scientific research on neurophysiology have proven emotions are not simply a minor aspect of human activity, but rather a fundamental one. This handbook provides comprehensive coverage and definitions of the most important issues, concepts, trends, and technologies in artificial emotions and related topics.
Описание: This collection of recently published and refereed papers comes from workshops and colloquia held over the last two years. The papers describe the development of command and control systems, military communications systems, information systems, surveillance systems, autonomous vehicles, simulators, and HCI.
Автор: Valentina Emilia Balas; Sanjiban Sekhar Roy; Dharm Название: Handbook of Deep Learning Applications ISBN: 3030114783 ISBN-13(EAN): 9783030114787 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.
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