deep learning edge computing (67 resultados)

1st ed. 2021. XII, 279 p. Hardcover. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

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paperback. Condición: Very Good.

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Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. The increasing demand for edge computing has created a pressing need for deep learning-based solutions capable of handling complex computational tasks in real-time. Deep Learning in Edge Computing Devices provides a comprehensive framework for designing and optimizing deep learning-based systems for edge computing devices. By exploring the intersection of deep learning and edge computing, this book offers a detailed guide to developing efficient and accurate deep learning-based systems. With its focus on practical implementation and real-world applications, Deep Learning in Edge Computing Devices is an indispensable resource for researchers and engineers seeking to unlock the full potential of deep learning in edge computing. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Edge computing has the potential to transform industries and revolutionize our understanding of the world around us. In 'Deep Learning for Edge Computing', the authors explore the exciting intersection of deep learning and edge computing. By applying neural networks to the analysis of edge computing performance and resource allocation, researchers can now accurately predict and optimize edge computing performance. This book provides a comprehensive introduction to the field, covering the fundamentals of deep learning, edge computing, and their intersection. It also delves into the latest advancements in edge computing task prediction, resource allocation, and optimization. With its clear explanations, practical examples, and cutting-edge research, 'Deep Learning for Edge Computing' is an essential resource for edge computing engineers, researchers, and scientists seeking to unlock the full potential of deep learning in their field. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Edge Computing for Deep Learning Applications is a comprehensive guide to the cutting-edge field of edge computing for deep learning. This book provides a thorough understanding of the principles and techniques behind edge computing for deep learning, and how they can be applied to real-world problems. With a focus on practical implementation, the author walks readers through the process of designing and training edge computing models for deep learning, and demonstrates their effectiveness in a variety of applications. By mastering the art of edge computing for deep learning, readers can unlock new insights and discoveries in their field, and develop more sophisticated AI systems. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Parallel Algorithms for Deep Learning in Edge Computing presents a comprehensive overview of the latest advances in parallel algorithms for deep learning in edge computing. By examining the complex relationships between parallel processing, deep learning, and edge computing, this book reveals the potential for parallel algorithms to play a critical role in improving the efficiency and effectiveness of deep learning systems in edge computing environments. From the development of novel parallel processing architectures to the creation of more effective deep learning models, Parallel Algorithms for Deep Learning in Edge Computing offers a cutting-edge analysis of the latest research and applications in this rapidly evolving field. By highlighting the importance of parallel algorithms in deep learning, this book provides a compelling case for the need for more sophisticated and effective parallel processing systems. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Deep learning is a powerful tool for a wide range of applications, from image recognition to natural language processing. However, its high computational requirements can make it challenging to deploy in real-world settings. 'Parallel Algorithms for Deep Learning in Edge Computing' explores the latest techniques and innovations in parallel algorithms, from the use of distributed computing to the development of new optimization methods. By examining real-world case studies and cutting-edge research, this book provides a comprehensive guide to parallel algorithms for deep learning in edge computing. With its unique blend of theory and practice, 'Parallel Algorithms' is an essential resource for anyone looking to stay ahead of the curve in this exciting field. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

paperback. Condición: New. Paperback. Pub Date: 2020-01-01 Pages: 706 Language: Chinese Publisher: Mechanical Industry Press Deep Neural Networks on Mobile Platforms (Principle Architecture and Optimization)/Intelligent Systems and Technology Series: Deep Neural Networks on Mobile Platforms (Principle Architecture and Optimization)/Intelligent Systems and Technology Series Intensively talks about the algorithm. instruction set. neural network design and actual combat. massive data processing. mainstream framework tailo.