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Titlebook: Embedded Artificial Intelligence; Principles, Platform Bin Li Book 2024 Tsinghua University Press, Beijing China. 2024 Embedded Artificial

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发表于 2025-3-21 16:29:33 | 显示全部楼层 |阅读模式
书目名称Embedded Artificial Intelligence
副标题Principles, Platform
编辑Bin Li
视频video
概述Offers a comprehensive introduction to embedded artificial intelligence with a clear and logical structure.Provides rich and in-depth coverage of embedded AI principles, platforms, and practical aspec
图书封面Titlebook: Embedded Artificial Intelligence; Principles, Platform Bin Li Book 2024 Tsinghua University Press, Beijing China. 2024 Embedded Artificial
描述.This book focuses on the emerging topic of embedded artificial intelligence and provides a systematic summary of its principles, platforms, and practices. In the section on principles, it analyzes three main approaches for implementing embedded artificial intelligence: cloud computing mode, local mode, and local-cloud collaborative mode. The book identifies five essential components for implementing embedded artificial intelligence: embedded AI accelerator chips, lightweight neural network algorithms, model compression techniques, compiler optimization techniques, and multi-level cascaded application frameworks. The platform section introduces mainstream embedded AI accelerator chips and software frameworks currently used in the industry. The practical part outlines the development process of embedded artificial intelligence and showcases real-world application examples with accompanying code...As a comprehensive guide to the emerging field of embedded artificial intelligence, the book offers rich and in-depth content, a clear and logical structure, and a balanced approach to both theoretical analysis and practical applications. It provides significant reference value and can serv
出版日期Book 2024
关键词Embedded Artificial Intelligence; Embedded AI; Edge AI; TinyML; Model Compression; Embedded AI Accelerato
版次1
doihttps://doi.org/10.1007/978-981-97-5038-2
isbn_softcover978-981-97-5037-5
isbn_ebook978-981-97-5038-2
copyrightTsinghua University Press, Beijing China. 2024
The information of publication is updating

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发表于 2025-3-21 23:10:20 | 显示全部楼层
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e, the book offers rich and in-depth content, a clear and logical structure, and a balanced approach to both theoretical analysis and practical applications. It provides significant reference value and can serv978-981-97-5037-5978-981-97-5038-2
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Problems of Political Theory and Action compression compilation co-design method. This method can effectively optimize the size and speed of deep neural network models and greatly shorten the adjustment time of the compression process, thereby enabling the deployment of deep neural network models on embedded devices.
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Compression of Deep Neural Network compression compilation co-design method. This method can effectively optimize the size and speed of deep neural network models and greatly shorten the adjustment time of the compression process, thereby enabling the deployment of deep neural network models on embedded devices.
发表于 2025-3-22 23:45:58 | 显示全部楼层
Software Framework for Embedded Neural Networksingly important for running inference models. Some hardware accelerators have launched supporting software development frameworks, such as NVIDIA’s TensorRT. There are also some manufacturers that have launched general embedded neural network software frameworks, such as TensorFlow Lite. They are introduced separately below.
发表于 2025-3-23 04:59:02 | 显示全部楼层
Book 2024ices. In the section on principles, it analyzes three main approaches for implementing embedded artificial intelligence: cloud computing mode, local mode, and local-cloud collaborative mode. The book identifies five essential components for implementing embedded artificial intelligence: embedded AI
发表于 2025-3-23 09:22:49 | 显示全部楼层
ge of embedded AI principles, platforms, and practical aspec.This book focuses on the emerging topic of embedded artificial intelligence and provides a systematic summary of its principles, platforms, and practices. In the section on principles, it analyzes three main approaches for implementing emb
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