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.

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.

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 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 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.

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.

These are the proceedings of the International Conference on ISMAC-CVB, held in Palladam, India, in May 2018. The book focuses on research to design new analysis paradigms and computational solutions for quantification of information provided by object recognition, scene understanding of computer vision and different algorithms like convolutional neural networks to allow computers to recognize and detect objects in images with unprecedented accuracy and to even understand the relationships between them. The proceedings treat the convergence of ISMAC in Computational Vision and Bioengineering technology and includes ideas and techniques like 3D sensing, human visual perception, scene understanding, human motion detection and analysis, visualization and graphical data presentation and a very wide range of sensor modalities in terms of surveillance, wearable applications, home automation etc. ISMAC-CVB is a forum for leading academic scientists, researchers and research scholars to exchange and share their experiences and research results about all aspects of computational vision and bioengineering.