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This new volume, Deep Learning in Visual Computing and Signal
Processing, covers the fundamentals and advanced topics in
designing and deploying techniques using deep architectures and
their application in visual computing and signal processing. The
volume first lays out the fundamentals of deep learning as well as
deep learning architectures and frameworks. It goes on to discuss
deep learning in neural networks and deep learning for object
recognition and detection models. It looks at the various specific
applications of deep learning in visual and signal processing, such
as in biorobotics, for automated brain tumor segmentation in MRI
images, in neural networks for use in seizure classification, for
digital forensic investigation based on deep learning, and more.
Key features: Covers both the fundamentals and the latest concepts
in deep learning Presents some of the diverse applications of deep
learning in visual computing and signal processing Includes over 90
figures and tables to elucidate the text An enlightening
amalgamation of deep learning concepts with visual computing and
signal processing applications, this valuable resource will serve
as a guide for researchers, engineers, and students who want to
have a quick start on learning and/or building deep learning
systems. It provides a good theoretical and practical understanding
and complete information and knowledge required to understand and
build deep learning models from scratch.
This book is a collection of accepted papers that were presented at
the International Conference on Communication and Computing Systems
(ICCCS-2016), Dronacharya College of Engineering, Gurgaon,
September 9-11, 2016. The purpose of the conference was to provide
a platform for interaction between scientists from industry,
academia and other areas of society to discuss the current
advancements in the field of communication and computing systems.
The papers submitted to the proceedings were peer-reviewed by 2-3
expert referees. This volume contains 5 main subject areas: 1.
Signal and Image Processing, 2. Communication & Computer
Networks, 3. Soft Computing, Intelligent System, Machine Vision and
Artificial Neural Network, 4. VLSI & Embedded System, 5.
Software Engineering and Emerging Technologies.
This new volume discusses the applications and challenges of deep
learning and the internet of things for applications in healthcare.
It describes deep learning techniques in conjunction with IoT used
by practitioners and researchers worldwide. The authors explore the
convergence of IoT and deep learning to enable things to
communicate, share information, and coordinate decisions. The book
includes deep feedforward networks, regularization, optimization
algorithms, convolutional networks, sequence modeling, and
practical methodology. Chapters look at assistive devices in
healthcare, alerting and detection devices, energy efficiency in
using IoT, data mining for gathering health information for
individuals with autism, IoT for mobile applications, and more. The
text also offers mathematical and conceptual background that
presents the latest technology as well as a selection of case
studies.
Cyber-Physical Systems (CPS) integrate computing and communication
capabilities by monitoring and controlling the physical systems via
embedded hardware and computers. This book brings together new and
futuristic findings on IoT, Cyber Physical Systems and Robotics
leading towards Automation and solving issues of various critical
applications in Real-time. The book initially overviews the
concepts of IoT, IIoT and Cyber Physical Systems followed by
various critical applications and discusses the latest designs and
developments that provide common solutions for the convergence of
technologies. In addition, the book specifies methodologies,
algorithms and other relevant architectures in various fields that
include Automation, Robotics, Smart Agriculture and Industry 4.0.
The book is intended for practitioners, enterprise representatives,
scientists, students and Ph.D Scholars in hopes of steering
research further towards cyber physical systems design and
development and implementation across various domains.
Additionally, this book can be used as a secondary reference, or
rather one-stop guide, by professionals for real-life
implementation of cyber physical systems. The book highlights: * A
Critical Coverage of various domains: IoT, Cyber Physical Systems,
Industry 4.0, Smart Automation and related critical applications. *
Advanced elaborations for target audiences to understand the
conceptual methodology and future directions of cyber physical
systems and IoT. * An approach towards Research Orientations to
enable researchers to point out areas and scope for implementation
of Cyber Physical Systems in several domains for better
productivity.
This book is a collection of accepted papers that were presented at
the International Conference on Communication and Computing Systems
(ICCCS-2016), Dronacharya College of Engineering, Gurgaon,
September 9-11, 2016. The purpose of the conference was to provide
a platform for interaction between scientists from industry,
academia and other areas of society to discuss the current
advancements in the field of communication and computing systems.
The papers submitted to the proceedings were peer-reviewed by 2-3
expert referees. This volume contains 5 main subject areas: 1.
Signal and Image Processing, 2. Communication & Computer
Networks, 3. Soft Computing, Intelligent System, Machine Vision and
Artificial Neural Network, 4. VLSI & Embedded System, 5.
Software Engineering and Emerging Technologies.
Machine Learning and the Internet of Medical Things in Healthcare
discusses the applications and challenges of machine learning for
healthcare applications. The book provides a platform for
presenting machine learning-enabled healthcare techniques and
offers a mathematical and conceptual background of the latest
technology. It describes machine learning techniques along with the
emerging platform of the Internet of Medical Things used by
practitioners and researchers worldwide. The book includes deep
feed forward networks, regularization, optimization algorithms,
convolutional networks, sequence modeling, and practical
methodology. It also presents the concepts of the Internet of
Things, the set of technologies that develops traditional devices
into smart devices. Finally, the book offers research perspectives,
covering the convergence of machine learning and IoT. It also
presents the application of these technologies in the development
of healthcare frameworks.
This book contains seven chapters encircles comprehensive study on
unsupervised change detection from remote sensing images for
research scholar .Change detection (CD) is a very important topic
in remote sensing for observing the earth .Change detection can be
performed by two methods namely supervised and unsupervised
Classification.We hope that the book will certainly adequate and
systematic knowledge to the readers .Any suggestions to the
improvement of this book will be highly appreciated.
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