Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing: Hardware Architectures (1st ed. 2024)
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- Synopsis
- 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.
- Copyright:
- 2024
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783031195686
- Related ISBNs:
- 9783031195679
- Publisher:
- Springer International Publishing
- Date of Addition:
- 11/01/23
- Copyrighted By:
- The Editor
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Computers and Internet, Technology
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
- Edited by:
- Sudeep Pasricha
- Edited by:
- Muhammad Shafique
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- by Sudeep Pasricha
- by Muhammad Shafique
- in Nonfiction
- in Computers and Internet
- in Technology