De Aller-Bedste Bøger - over 12 mio. danske og engelske bøger
Levering: 1 - 2 hverdage

Methods and Techniques in Deep Learning

Bag om Methods and Techniques in Deep Learning

Methods and Techniques in Deep Learning Introduces multiple state-of-the-art deep learning architectures for mmWave radar in a variety of advanced applications Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions provides a timely and authoritative overview of the use of artificial intelligence (AI)-based processing for various mmWave radar applications. Focusing on practical deep learning techniques, this comprehensive volume explains the fundamentals of deep learning, reviews cutting-edge deep metric learning techniques, describes different typologies of reinforcement learning (RL) algorithms, highlights how domain adaptation (DA) can be used for improving the performance of machine learning (ML) algorithms, and more. Throughout the book, readers are exposed to product-ready deep learning solutions while learning skills that are relevant for building any industrial-grade, sensor-based deep learning solution. A team of authors with more than 70 filed patents and 100 published papers on AI and sensor processing illustrates how deep learning is enabling a range of advanced industrial, consumer, and automotive applications of mmWave radars. In-depth chapters cover topics including multi-modal deep learning approaches, the elemental blocks required to formulate Bayesian deep learning, how domain adaptation (DA) can be used for improving the performance of machine learning algorithms, and geometric deep learning are used for processing point clouds. In addition, the book: * Discusses various advanced applications and how their respective challenges have been addressed using different deep learning architectures and algorithms * Describes deep learning in the context of computer vision, natural language processing, sensor processing, and mmWave radar sensors * Demonstrates how deep parametric learning reduces the number of trainable parameters and improves the data flow * Presents several human-machine interface (HMI) applications such as gesture recognition, human activity classification, human localization and tracking, in-cabin automotive occupancy sensing Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions is an invaluable resource for industry professionals, researchers, and graduate students working in systems engineering, signal processing, sensors, data science, and AI.

Vis mere
  • Sprog:
  • Engelsk
  • ISBN:
  • 9781119910657
  • Indbinding:
  • Hardback
  • Sideantal:
  • 336
  • Udgivet:
  • 8. december 2022
  • Størrelse:
  • 157x23x235 mm.
  • Vægt:
  • 643 g.
  • 2-3 uger.
  • 21. januar 2025
På lager
Forlænget returret til d. 31. januar 2025
  •  

    Kan ikke leveres inden jul.
    Køb nu og print et gavebevis

Normalpris

Abonnementspris

- Rabat på køb af fysiske bøger
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding

Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.

Beskrivelse af Methods and Techniques in Deep Learning

Methods and Techniques in Deep Learning
Introduces multiple state-of-the-art deep learning architectures for mmWave radar in a variety of advanced applications
Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions provides a timely and authoritative overview of the use of artificial intelligence (AI)-based processing for various mmWave radar applications. Focusing on practical deep learning techniques, this comprehensive volume explains the fundamentals of deep learning, reviews cutting-edge deep metric learning techniques, describes different typologies of reinforcement learning (RL) algorithms, highlights how domain adaptation (DA) can be used for improving the performance of machine learning (ML) algorithms, and more. Throughout the book, readers are exposed to product-ready deep learning solutions while learning skills that are relevant for building any industrial-grade, sensor-based deep learning solution.
A team of authors with more than 70 filed patents and 100 published papers on AI and sensor processing illustrates how deep learning is enabling a range of advanced industrial, consumer, and automotive applications of mmWave radars. In-depth chapters cover topics including multi-modal deep learning approaches, the elemental blocks required to formulate Bayesian deep learning, how domain adaptation (DA) can be used for improving the performance of machine learning algorithms, and geometric deep learning are used for processing point clouds. In addition, the book:
* Discusses various advanced applications and how their respective challenges have been addressed using different deep learning architectures and algorithms
* Describes deep learning in the context of computer vision, natural language processing, sensor processing, and mmWave radar sensors
* Demonstrates how deep parametric learning reduces the number of trainable parameters and improves the data flow
* Presents several human-machine interface (HMI) applications such as gesture recognition, human activity classification, human localization and tracking, in-cabin automotive occupancy sensing
Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions is an invaluable resource for industry professionals, researchers, and graduate students working in systems engineering, signal processing, sensors, data science, and AI.

Brugerbedømmelser af Methods and Techniques in Deep Learning



Find lignende bøger
Bogen Methods and Techniques in Deep Learning findes i følgende kategorier: