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This book includes novel and state-of-the-art research discussions
that articulate and report all research aspects, including
theoretical and experimental prototypes and applications that
incorporate sustainability into emerging applications. In recent
years, sustainability and information and communication
technologies (ICT) are highly intertwined, where sustainability
resources and its management has attracted various researchers,
stakeholders, and industrialists. The energy-efficient
communication technologies have revolutionized the various smart
applications like smart cities, healthcare, entertainment, and
business. The book discusses and articulates emerging challenges in
significantly reducing the energy consumption of communication
systems and also explains development of a sustainable and
energy-efficient mobile and wireless communication network. It
includes best selected high-quality conference papers in different
fields such as internet of things, cloud computing, data mining,
artificial intelligence, machine learning, autonomous systems, deep
learning, neural networks, renewable energy sources, sustainable
wireless communication networks, QoS, network sustainability, and
many other related areas.
This book includes selected papers from the 4th International
Conference on Computational Vision and Bio Inspired Computing
(ICCVBIC 2020), held in Coimbatore, India, from November 19 to 20,
2020. This proceedings book presents state-of-the-art research
innovations in computational vision and bio-inspired techniques.
The book reveals the theoretical and practical aspects of
bio-inspired computing techniques, like machine learning,
sensor-based models, evolutionary optimization and big data
modeling and management that make use of effectual computing
processes in the bio-inspired systems. As such it contributes to
the novel research that focuses on developing bio-inspired
computing solutions for various domains, such as human-computer
interaction, image processing, sensor-based single processing,
recommender systems and facial recognition, which play an
indispensable part in smart agriculture, smart city, biomedical and
business intelligence applications.
This book includes novel and state-of-the-art research discussions
that articulate and report all research aspects, including
theoretical and experimental prototypes and applications that
incorporate sustainability into emerging applications. In recent
years, sustainability and information and communication
technologies (ICT) are highly intertwined, where sustainability
resources and its management has attracted various researchers,
stakeholders, and industrialists. The energy-efficient
communication technologies have revolutionized the various smart
applications like smart cities, healthcare, entertainment, and
business. The book discusses and articulates emerging challenges in
significantly reducing the energy consumption of communication
systems and also explains development of a sustainable and
energy-efficient mobile and wireless communication network. It
includes best selected high-quality conference papers in different
fields such as internet of things, cloud computing, data mining,
artificial intelligence, machine learning, autonomous systems, deep
learning, neural networks, renewable energy sources, sustainable
wireless communication networks, QoS, network sustainability, and
many other related areas.
This book provides a collection of the state-of-the-art research
attempts to tackle the challenges in image and signal processing
from various novel and potential research perspectives. The book
investigates feature extraction techniques, image enhancement
methods, reconstruction models, object detection methods,
recommendation models, deep and temporal feature analysis,
intelligent decision support systems, and autonomous image
detection models. In addition to this, the book also looks into the
potential opportunities to monitor and control the global pandemic
situations. Image processing technology has progressed
significantly in recent years, and it has been commercialized
worldwide to provide superior performance with enhanced
computer/machine vision, video processing, and pattern recognition
capabilities. Meanwhile, machine learning systems like CNN and
CapsNet get popular to provide better model hierarchical
relationships and attempts to more closely mimic biological neural
organization. As machine learning systems prosper, image processing
and machine learning techniques will be tightly intertwined and
continuously promote each other in real-world settings. Adopting
this trend, however, the image processing researchers are faced
with few image reconstruction, analysis, and segmentation
challenges. On the application side, the orientation of the image
features and noise removal has become a huge burden.
This book gathers selected papers presented at the Inventive
Communication and Computational Technologies conference (ICICCT
2021), held on 25-26 June 2021 at Gnanamani College of Technology,
Tamil Nadu, India. The book covers the topics such as Internet of
things, social networks, mobile communications, big data analytics,
bio-inspired computing, and cloud computing. The book is
exclusively intended for academics and practitioners working to
resolve practical issues in this area.
This book features selected papers from the International
Conference on Soft Computing for Security Applications (ICSCS
2021), held at Dhirajlal Gandhi College of Technology, Tamil Nadu,
India, during June 2021. It covers recent advances in the field of
soft computing techniques such as fuzzy logic, neural network,
support vector machines, evolutionary computation, machine learning
and probabilistic reasoning to solve various real-time challenges.
The book presents innovative work by leading academics,
researchers, and experts from industry.
Machine Learning in Bio-Signal Analysis and Diagnostic Imaging
presents original research on the advanced analysis and
classification techniques of biomedical signals and images that
cover both supervised and unsupervised machine learning models,
standards, algorithms, and their applications, along with the
difficulties and challenges faced by healthcare professionals in
analyzing biomedical signals and diagnostic images. These
intelligent recommender systems are designed based on machine
learning, soft computing, computer vision, artificial intelligence
and data mining techniques. Classification and clustering
techniques, such as PCA, SVM, techniques, Naive Bayes, Neural
Network, Decision trees, and Association Rule Mining are among the
approaches presented. The design of high accuracy decision support
systems assists and eases the job of healthcare practitioners and
suits a variety of applications. Integrating Machine Learning (ML)
technology with human visual psychometrics helps to meet the
demands of radiologists in improving the efficiency and quality of
diagnosis in dealing with unique and complex diseases in real time
by reducing human errors and allowing fast and rigorous analysis.
The book's target audience includes professors and students in
biomedical engineering and medical schools, researchers and
engineers.
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