Vor Ort
Merkzettel Warenkorb
  • Produktbild: AI for Emerging Verticals
  • Produktbild: AI for Emerging Verticals

AI for Emerging Verticals Human-Robot Computing, Sensing and Networking

147,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

29.01.2021

Herausgeber

Muhammad Zeeshan Shakir + weitere

Verlag

Institution of Engineering & Technology

Seitenzahl

386

Maße (L/B/H)

23,9/16,3/2,3 cm

Gewicht

771 g

Sprache

Englisch

ISBN

978-1-78561-982-3

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

29.01.2021

Herausgeber

Verlag

Institution of Engineering & Technology

Seitenzahl

386

Maße (L/B/H)

23,9/16,3/2,3 cm

Gewicht

771 g

Sprache

Englisch

ISBN

978-1-78561-982-3

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

Noch keine Bewertungen vorhanden

Verfassen Sie die erste Bewertung zu diesem Artikel

Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.

Kundinnen und Kunden meinen

Bewertungen (0)
  • Produktbild: AI for Emerging Verticals
  • Produktbild: AI for Emerging Verticals

    • Part I: Human-robot
      • Chapter 1: Deep learning techniques for modelling human manipulation and its translation for autonomous robotic grasping with soft end-effectors
      • Chapter 2: Artificial intelligence for affective computing: an emotion recognition case study
      • Chapter 3: Machine learning-based affect detection within the context of human-horse interaction
      • Chapter 4: Robot intelligence for real-world applications
      • Chapter 5: Visual object tracking by quadrotor AR.Drone using artificial neural networks and fuzzy logic controller
    • Part II: Network
      • Chapter 6: Predictive mobility management in cellular networks
      • Chapter 7: Artificial intelligence and data analytics in 5G and beyond-5G wireless networks
      • Chapter 8: Deep Q-network-based coverage hole detection for future wireless networks
      • Chapter 9: Artificial intelligence for localization of ultrawide bandwidth (UWB) sensor nodes
      • Chapter 10: A Cascaded Machine Learning Approach for indoor classification and localization using adaptive feature selection
    • Part III: Sensing
      • Chapter 11: EEG-based biometrics: effects of template ageing
      • Chapter 12: A machine-learning-driven solution to the problem of perceptual video quality metrics
      • Chapter 13: Multitask learning for autonomous driving
      • Chapter 14: Machine-learning-enabled ECG monitoring for early detection of hyperkalaemia
      • Chapter 15: Combining deterministic compressed sensing and machine learning for data reduction in connected health
      • Chapter 16: Large-scale distributed and scalable SOM-based architecture for high-dimensional data reduction
      • Chapter 17: Surface water pollution monitoring using the Internet of Things (IoT) and machine learning
      • Chapter 18: Conclusions