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This book discusses advanced technologies for applications in
renewable energy and power systems. The topics covered include
neural network applications in power electronics, deep learning
applications in power systems, design and simulation of multilevel
inverters, solid state transformers, neural network applications
for fault detection in power electronics, etc. The book also
discusses the important role of artificial intelligence in power
systems, and machine learning for renewable energy. This book will
be of interest to researchers, professionals, and technocrats
looking at power systems, power distribution, and grid operations.
This book discusses advanced technologies for applications in
renewable energy and power systems. The topics covered include
neural network applications in power electronics, deep learning
applications in power systems, design and simulation of multilevel
inverters, solid state transformers, neural network applications
for fault detection in power electronics, etc. The book also
discusses the important role of artificial intelligence in power
systems, and machine learning for renewable energy. This book will
be of interest to researchers, professionals, and technocrats
looking at power systems, power distribution, and grid operations.
The healthcare industry is predominantly moving towards affordable,
accessible, and quality health care. All organizations are striving
to build communication compatibility among the wide range of
devices that have operated independently. Recent developments in
electronic devices have boosted the research in the medical imaging
field. It incorporates several medical imaging techniques and
achieves an important goal for health improvement all over the
world. Despite the significant advances in high-resolution medical
instruments, physicians cannot always obtain the full amount of
information directly from the equipment outputs, and a large amount
of data cannot be easily exploited without a computer. Machine
Learning and AI Techniques in Interactive Medical Image Analysis
discusses how clinical efficiency can be improved by investigating
the different types of intelligent techniques and systems to get
more reliable and accurate diagnostic conclusions. This book
further introduces segmentation techniques to locate suspicious
areas in medical images and increase the segmentation accuracy.
Covering topics such as computer-aided detection, intelligent
techniques, and machine learning, this premier reference source is
a dynamic resource for IT specialists, computer scientists,
diagnosticians, imaging specialists, medical professionals,
hospital administrators, medical students, medical technicians,
librarians, researchers, and academicians.
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