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Methods and Techniques in Deep Learning - Advancements in mmWave Radar Solutions (Hardcover)
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Methods and Techniques in Deep Learning - Advancements in mmWave Radar Solutions (Hardcover)
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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.
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