Disruptive Trends in Computer Aided Diagnosis collates novel techniques and methodologies in the domain of content based image classification and deep learning/machine learning techniques to design efficient computer aided diagnosis architecture. It is aimed to highlight new challenges and probable solutions in the domain of computer aided diagnosis to leverage balancing of sustainable ecology. The volume focuses on designing efficient algorithms for proposing CAD systems to mitigate the challenges of critical illnesses at an early stage. State-of-the-art novel methods are explored for envisaging automated diagnosis systems thereby overriding the limitations due to lack of training data, sample annotation, region of interest identification, proper segmentation and so on. The assorted techniques addresses the challenges encountered in existing systems thereby facilitating accurate patient healthcare and diagnosis. Features: An integrated interdisciplinary approach to address complex computer aided diagnosis problems and limitations. Elucidates a rich summary of the state-of-the-art tools and techniques related to automated detection and diagnosis of life threatening diseases including pandemics. Machine learning and deep learning methodologies on evolving accurate and precise early detection and medical diagnosis systems. Information presented in an accessible way for students, researchers and medical practitioners. The volume would come to the benefit of both post-graduate students and aspiring researchers in the field of medical informatics, computer science and electronics and communication engineering. In addition, the volume is also intended to serve as a guiding factor for the medical practitioners and radiologists in accurate diagnosis of diseases.

This reference text presents the knowledge base of computer vision and soft computing techniques with their applications for sustainable developments. Features: ∙ Covers a variety of deep learning architectures useful for computer vision tasks. ∙ Demonstrates the use of different soft computing techniques and their applications for different computer vision tasks. ∙ Highlights the unified strengths of hybrid techniques based on deep learning and soft computing taken together that give the interpretable, adaptive, and optimized solution to a given problem. ∙ Addresses the different issues and further research opportunities in computer vision and soft computing. ∙ Describes all the concepts with practical examples and case studies with appropriate performance measures that validate the applicability of the respective technique to a certain domain. ∙ Considers recent real word problems and the prospective solutions to these problems. This book will be useful to researchers, students, faculty, and industry personnel who are eager to explore the power of deep learning and soft computing for different computer vision tasks.

Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data: COVID-19 and Beyond is a handy treatise to elicit and elaborate possible intelligent mechanisms for modeling, prediction, diagnosis, and early detection of diseases arising from outbreaks of different epidemics with special reference to COVID-19. Starting with a formal introduction of the human immune systems, this book focuses on the epidemiological aspects with due cognizance to modeling, prevention, and diagnosis of epidemics. In addition, it also deals with evolving decisions on post-pandemic socio-economic structure. The book offers a comprehensive coverage of the most essential topics, including: A general overview of pandemics and their outbreak behavior A detailed overview of CI techniques Intelligent modeling, prediction, and diagnostic measures for pandemics Prognostic models Post-pandemic socio-economic structure The accompanying case studies are based on available real-world data sets. While other books may deal with this COVID-19 pandemic, none features topics covering the human immune system as well as influences on the environmental disorder due to the ongoing pandemic. The book is primarily intended to benefit medical professionals and healthcare workers as well as the virologists who are essentially the frontline fighters of this pandemic. In addition, it also serves as a vital resource for relevant researchers in this interdisciplinary field as well as for tutors and postgraduate and undergraduate students of information sciences.

This text has attempted to collate quality research articles ranging from A Mathematical Disposition for Neural Nets, to Cognitive Computing, to Quantum Machine Learning, to a Multimodal Emotion Recognition System, to Responsible AI, to AI for Accessibility and Inclusion, to Artificial-Enabled Intelligence Enabled Applications in the sectors of Health, Pharma and Education. Features Focus on AI research and interdisciplinary research that exhibits AI inclusion to a greater degree Focus on application of disruptive technology in the context of the twenty-first century human and machine approach Focus on role of disruptive technology such as cognitive computing, quantum machine learning, IOT enabled-recognition systems Focus on unravelling the powerful features of artificial intelligence for societal benefits including accessibility This volume will cater as a ready reference to an individual’s quest for deep diving into the ocean of artificial intelligence-enabled solution approaches. The book will serve as a useful reference for researchers, innovators, academicians, entrepreneurs, and professionals aspiring to gain expertise in the domain of cognitive and quantum computing, IOT-enabled intelligent systems and so on.

Computational Intelligence in Image and Video Processing presents introduction, state-of-the-art and adaptations of computational intelligence techniques and their usefulness in image and video enhancement, classification, retrieval, forensics and captioning. It covers an amalgamation of such techniques in diverse applications of image and video processing. Features: A systematic overview of state-of-the-art technology in computational intelligence techniques for image and video processing Advanced evolutionary and nature-inspired approaches to solve optimization problems in the image and video processing domain Outcomes of recent research and some pointers to future advancements in image and video processing and intelligent solutions using computational intelligence techniques Code snippets of the computational intelligence algorithm/techniques used in image and video processing This book is primarily aimed at advanced undergraduates, graduates and researchers in computer science and information technology. Engineers and industry professionals will also find this book useful.

Blockchain for IoT provides the basic concepts of Blockchain technology and its applications to varied domains catering to socio-technical fields. It also introduces intelligent Blockchain platforms by way of infusing elements of computational intelligence into Blockchain technology. With the help of an interdisciplinary approach, it includes insights into real-life IoT applications to enable the readers to assimilate the concepts with ease. This book provides a balanced approach between theoretical understanding and practical applications. Features: A self-contained approach to integrating the principles of Blockchain with elements of computational intelligence A rich and novel foundation of Blockchain technology with reference to the internet of things conjoined with the tenets of artificial intelligence in yielding intelligent Blockchain platforms Elucidates essential background, concepts, definitions, and theories thereby putting forward a complete treatment on the subject Information presented in an accessible way for research students of computer science and information technology, as well as software professionals who can inherit the much-needed developmental ideas to boost up their computing knowledge on distributed platforms This book is aimed primarily at undergraduates, postgraduates, and researchers studying Blockchain.

Intelligent Cyber-Physical Systems Security for Industry 4.0: Applications, Challenges and Management presents new cyber-physical security findings for Industry 4.0 using emerging technologies like artificial intelligence (with machine/deep learning), data mining, applied mathematics. All these are the essential components for processing data, recognizing patterns, modeling new techniques, and improving the advantages of data science. Features • Presents an integrated approach with Cyber-Physical Systems, CPS security, and Industry 4.0 in one place • Exposes the necessity of security initiatives, standards, security policies, and procedures in the context of industry 4.0 • Suggests solutions for enhancing the protection of 5G and the Internet of Things (IoT) security • Promotes how optimization or intelligent techniques envisage the role of artificial intelligence-machine/deep learning (AI-ML/DL) in cyberphysical systems security for industry 4.0 This book is primarily aimed at graduates, researchers and professionals working in the field of security. Executives concerned with security management, knowledge dissemination, information, and policy development for data and network security in different educational, government, and non-government organizations will also find this book useful.