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Applying mechanisms and principles of human intelligence and converging the brain and artificial intelligence (AI) is currently a research trend. The applications of AI in brain simulation are countless. Brain-inspired intelligent systems will improve next-generation information processing by applying theories, techniques, and applications inspired by the information processing principles from the brain. Exploring Future Opportunities of Brain-Inspired Artificial Intelligence focuses on the convergence of AI with brain-inspired intelligence. It presents research on brain-inspired cognitive machines with vision, audition, language processing, and thinking capabilities. Covering topics such as data analysis tools, knowledge representation, and super-resolution, this premier reference source is an essential resource for engineers, developers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.
As social robots and the artificial intelligence (AI) that powers them become more advanced, they will likely take on more social and work roles. There is a variety of ways social robots can be engaged in human life, and they can leave an impact in terms of ease of use, productivity, and human support. The interactivity and receptivity of social robots can encourage humans to form social relationships with them. But now robots are intended to perform socially intelligent and interactive services like reception, guidance, emotional companionship, and more, which makes social human-robot interaction essential to help improve aspects of quality of life as well as to improve the efficiency of hu...
The book is a collection of high-quality peer-reviewed research papers presented at the Fourth International Conference on Innovations in Computer Science and Engineering (ICICSE 2016) held at Guru Nanak Institutions, Hyderabad, India during 22 – 23 July 2016. The book discusses a wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academic and industry present their original work and exchange ideas, information, techniques and applications in the field of data science and analytics, artificial intelligence and expert systems, mobility, cloud computing, network security, and emerging technologies.
In this book, we embark on a journey into the realm of predictive data modeling for biomedical data and imaging in healthcare. It explores the potential of predictive analytics in the field of medical science through utilizing various tools and techniques to unravel insights and enhance patient care. This volume creates a medium for an interchange of knowledge from expertise and concerns in the field of predictive data modeling. In detail, the research work on this will include the effective use of predictive data modeling algorithms to run image analysis tasks for understanding. Predictive Data Modelling for Biomedical Data and Imaging is divided into three sections, namely Section I – Be...
Health surveillance and intelligence play an important role in modern health systems as more data must be collected and analyzed. It is crucial that this data is interpreted and analyzed effectively and efficiently in order to assist with diagnoses and predictions. Diagnostic Applications of Health Intelligence and Surveillance Systems is an essential reference book that examines recent studies that are driving artificial intelligence in the health sector and helping practitioners to predict and diagnose diseases. Chapters within the book focus on health intelligence and how health surveillance data can be made useful and meaningful. Covering topics that include computational intelligence, data analytics, mobile health, and neural networks, this book is crucial for healthcare practitioners, IT specialists, academicians, researchers, and students.
This two-volume set (CCIS 1229 and CCIS 1230) constitutes the refereed proceedings of the 5th International Conference on Recent Developments in Science, Engineering and Technology, REDSET 2019, held in Gurugram, India, in November 2019. The 74 revised full papers presented were carefully reviewed and selected from total 353 submissions. The papers are organized in topical sections on data centric programming; next generation computing; social and web analytics; security in data science analytics; big data analytics.
With the development of innovative technologies, the study of industrial automation is obtaining extraordinary attention from academia, governments, researchers, and various industrial communities. The technical innovations in advanced technologies such as deep learning, blockchain, artificial intelligence of things (AIOT), and more have unlocked the potential for bringing intelligent automation and efficiency to the industries to control their various operations. These new technologies provide an efficient and secure way for industries to manage and develop products intelligently. Revolutionizing Industrial Automation Through the Convergence of Artificial Intelligence and the Internet of Th...
This book presents high-quality, original contributions (both theoretical and experimental) on Information Security, Machine Learning, Data Mining and Internet of Things (IoT). It gathers papers presented at ICETIT 2019, the 1st International Conference on Emerging Trends in Information Technology, which was held in Delhi, India, in June 2019. This conference series represents a targeted response to the growing need for research that reports on and assesses the practical implications of IoT and network technologies, AI and machine learning, data analytics and cloud computing, security and privacy, and next generation computing technologies.
Artificial intelligence (AI) is influencing the future of almost every sector and human being. AI has been the primary driving force behind emerging technologies such as big data, blockchain, robots, and the internet of things (IoT), and it will continue to be a technological innovator for the foreseeable future. New algorithms in AI are changing business processes and deploying AI-based applications in various sectors. The Handbook of Research on AI and Knowledge Engineering for Real-Time Business Intelligence is a comprehensive reference that presents cases and best practices of AI and knowledge engineering applications on business intelligence. Covering topics such as deep learning methods, face recognition, and sentiment analysis, this major reference work is a dynamic resource for business leaders and executives, IT managers, AI scientists, students and educators of higher education, librarians, researchers, and academicians.