This book provides the reader with the fundamental knowledge in the
area of deep learning with application to visual content mining.
The authors give a fresh view on Deep learning approaches both from
the point of view of image understanding and supervised machine
learning. It contains chapters which introduce theoretical and
mathematical foundations of neural networks and related
optimization methods. Then it discusses some particular very
popular architectures used in the domain: convolutional neural
networks and recurrent neural networks. Deep Learning is currently
at the heart of most cutting edge technologies. It is in the core
of the recent advances in Artificial Intelligence. Visual
information in Digital form is constantly growing in volume. In
such active domains as Computer Vision and Robotics visual
information understanding is based on the use of deep learning.
Other chapters present applications of deep learning for visual
content mining. These include attention mechanisms in deep neural
networks and application to digital cultural content mining. An
additional application field is also discussed, and illustrates how
deep learning can be of very high interest to computer-aided
diagnostics of Alzheimer's disease on multimodal imaging. This book
targets advanced-level students studying computer science including
computer vision, data analytics and multimedia. Researchers and
professionals working in computer science, signal and image
processing may also be interested in this book.
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