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Deepfakes is a synthetic media that leverage powerful Artificial Intelligence (AI) and machine learning (ML) techniques to generate fake visual and audio content that are extremely realistic, thus making it very hard for a human to distinguish from the original ones. Apart from technological introduction to the Deepfakes concept, the book details algorithms to detect Deepfakes, techniques for identifying manipulated content and identifying face swap, generative adversarial neural networks, media forensic techniques, deep learning architectures, forensic analysis of DeepFakes and so forth. Provides a technical introduction to DeepFakes, its benefits, and the potential harms Presents practical...
Transportation typically entails crucial “life-death” choices, delegating crucial decisions to an AI algorithm without any explanation poses a serious threat. Hence, explainability and responsible AI is crucial in the context of intelligent transportation. In Intelligence Transportation System (ITS) implementations such as traffic management systems and autonomous driving applications, AI-based control mechanisms are gaining prominence. Explainable artificial intelligence for intelligent transportation system tackling certain challenges in the field of autonomous vehicle, traffic management system, data integration and analytics and monitor the surrounding environment. The book discusses and inform researchers on explainable Intelligent Transportation system. It also discusses prospective methods and techniques for enabling the interpretability of transportation systems. The book further focuses on ethical considerations apart from technical considerations.
This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example—a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovem...
Generative artificial intelligence (GAI) represents a profound leap in technological advancement, empowering machines to create content that closely mimics human creativity in various forms. As this technology continues to evolve and permeate multiple industries, it is essential to address the accompanying ethical considerations that arise from its use. Furthermore, there is a need for transparency in how GAI systems are developed and deployed to ensure that they are used responsibly and that their outputs are reliable and fair. Balancing innovation with ethical practices will be crucial to harnessing the benefits of GAI while mitigating its risks and ensuring its positive contribution to so...
Emerging Technologies for Health Literacy and Medical Practice unveils a transformative revolution brought about by emerging technologies, setting the stage for a paradigmatic shift from reactive medical interventions to proactive preventive measures. This transition has not only redefined the doctor-patient relationship but has also placed patients at the helm of their health management, actively engaged in informed decision-making. The book, a collective effort by experts across diverse disciplines, stands as an authoritative compendium delving into the profound implications of cutting-edge technologies in healthcare. From the tantalizing realm of artificial intelligence powering diagnosti...
The COVID-19 pandemic has highlighted the importance of health data, technology, and access to health informatics. The applications of several information technologies in the context of healthcare are proving instrumental in pandemic control. These technologies were already actively used in the healthcare sector before the pandemic. However, the pandemic has resulted in researchers reassessing how these technologies could have better assisted with the aftermath of the COVID-19 pandemic and how they may mitigate the threat of future pandemics. Health Informatics and Patient Safety in Times of Crisis provides a fresh perspective on how healthcare informatics has managed the current pandemic and how improved healthcare informatics could help in a future crisis. Covering topics such as digital public health, misinformation, and knowledge management, this premier reference source is an indispensable resource for medical professionals, hospital administrators, public health officials, community leaders, international leaders, libraries, medical students, medical professors, researchers, and academicians.
This book constitutes the refereed proceedings of the 5th International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2022, held in Kingsville, TX, USA, in collaboration with the Applied AI Research Laboratory of the University of South Dakota, during December 01-02, 2022. The 31 full papers included in this book were carefully reviewed and selected from 69 submissions. They were organized in topical sections as follows: healthcare: medical imaging and informatics; computer vision and pattern recognition; internet of things and security; and signal processing and machine learning.
This book offers crucial solutions and insights on how transportation companies can enhance their cybersecurity management and protect their corporate reputation and revenue from the increasing risk of cyberattacks. The movement of people and goods from one location to another has always been essential to human development and survival. People are now exploring new methods of carrying goods. Transportation infrastructure is critical to the growth of a global community that is more united and connected. The presented cybersecurity framework is an example of a risk-based method for managing cybersecurity risk. An organisation can find opportunities to strengthen and explain its management of c...
This book gathers selected papers presented at International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication (MARC 2020), held in Krishna Engineering College, Ghaziabad, India, during December 17–18, 2020. This book discusses key concepts, challenges, and potential solutions in connection with established and emerging topics in advanced computing, renewable energy, and network communications.