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Deep Learning-Based Face Analytics (Hardcover, 1st ed. 2021)
Loot Price: R4,923
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Deep Learning-Based Face Analytics (Hardcover, 1st ed. 2021)
Series: Advances in Computer Vision and Pattern Recognition
Expected to ship within 12 - 17 working days
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This book provides an overview of different deep learning-based
methods for face recognition and related problems. Specifically,
the authors present methods based on autoencoders, restricted
Boltzmann machines, and deep convolutional neural networks for face
detection, localization, tracking, recognition, etc. The authors
also discuss merits and drawbacks of available approaches and
identifies promising avenues of research in this rapidly evolving
field. Even though there have been a number of different approaches
proposed in the literature for face recognition based on deep
learning methods, there is not a single book available in the
literature that gives a complete overview of these methods. The
proposed book captures the state of the art in face recognition
using various deep learning methods, and it covers a variety of
different topics related to face recognition. This book is aimed at
graduate students studying electrical engineering and/or computer
science. Biometrics is a course that is widely offered at both
undergraduate and graduate levels at many institutions around the
world: This book can be used as a textbook for teaching topics
related to face recognition. In addition, the work is beneficial to
practitioners in industry who are working on biometrics-related
problems. The prerequisites for optimal use are the basic knowledge
of pattern recognition, machine learning, probability theory, and
linear algebra.
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