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Vision, Sensing and Analytics: Integrative Approaches

Om Vision, Sensing and Analytics: Integrative Approaches

This book serves as the first guideline of the integrative approach, optimal for our new and young generations. Recent technology advancements in computer vision, IoT sensors, and analytics open the door to highly impactful innovations and applications as a result of effective and efficient integration of those. Such integration has brought to scientists and engineers a new approach ¿the integrative approach. This offers far more rapid development and scalable architecting when comparing to the traditional hardcore developmental approach. Featuring biomedical and healthcare challenges including COVID-19, we present a collection of carefully selective cases with significant added- values as a result of integrations, e.g., sensing with AI, analytics with different data sources, and comprehensive monitoring with many different sensors, while sustaining its readability.

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  • Språk:
  • Engelska
  • ISBN:
  • 9783030754891
  • Format:
  • Inbunden
  • Sidor:
  • 413
  • Utgiven:
  • 6. juni 2021
  • Utgåva:
  • 12021
  • Mått:
  • 155x235x0 mm.
  • Vikt:
  • 799 g.
Leveranstid: 2-4 veckor
Förväntad leverans: 19. december 2024
Förlängd ångerrätt till 31. januari 2025

Beskrivning av Vision, Sensing and Analytics: Integrative Approaches

This book serves as the first guideline of the integrative approach, optimal for our new and young generations. Recent technology advancements in computer vision, IoT sensors, and analytics open the door to highly impactful innovations and applications as a result of effective and efficient integration of those. Such integration has brought to scientists and engineers a new approach ¿the integrative approach. This offers far more rapid development and scalable architecting when comparing to the traditional hardcore developmental approach.
Featuring biomedical and healthcare challenges including COVID-19, we present a collection of carefully selective cases with significant added- values as a result of integrations, e.g., sensing with AI, analytics with different data sources, and comprehensive monitoring with many different sensors, while sustaining its readability.

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