Deep Learning Model Optimization, Deployment and Improvement Techniques for Edge-native Applications

Released on by Pethuru Raj
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  • Deep Learning Model Optimization, Deployment and Improvement Techniques for Edge-native Applications Book Detail

  • Author : Pethuru Raj
  • Release Date : 2024-08-22
  • Publisher : Cambridge Scholars Publishing
  • Genre : Computers
  • Pages : 427
  • ISBN 13 : 1036409619
  • File Size : 65,65 MB
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Deep Learning Model Optimization, Deployment and Improvement Techniques for Edge-native Applications by Pethuru Raj PDF Summary

Book Description: The edge AI implementation technologies are fast maturing and stabilizing. Edge AI digitally transforms retail, manufacturing, healthcare, financial services, transportation, telecommunication, and energy. The transformative potential of Edge AI, a pivotal force in driving the evolution from Industry 4.0’s smart manufacturing and automation to Industry 5.0’s human-centric, sustainable innovation. The exploration of the cutting-edge technologies, tools, and applications that enable real-time data processing and intelligent decision-making at the network’s edge, addressing the increasing demand for efficiency, resilience, and personalization in industrial systems. Our book aims to provide readers with a comprehensive understanding of how Edge AI integrates with existing infrastructures, enhances operational capabilities, and fosters a symbiotic relationship between human expertise and machine intelligence. Through detailed case studies, technical insights, and practical guidelines, this book serves as an essential resource for professionals, researchers, and enthusiasts poised to harness the full potential of Edge AI in the rapidly advancing industrial landscape.

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Deep Learning on Edge Computing Devices

Deep Learning on Edge Computing Devices

File Size : 8,8 MB
Total View : 4776 Views
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Deep Learning on Edge Computing Devices: Design Challenges of Algorithm and Architecture focuses on hardware architecture and embedded deep learning, including