Hardcover. This book comprehensively covers designing and implementing misinformation intervention strategies and risk communication approaches for generative artificial intelligence (AI) technologies. Key Features:Showcases cuttingedge technology and offers insights into one of the most rapidly evolving fields in AIProvides a comprehensive understanding of the underlying principles, algorithms, and applications of this cuttingedge technology, offering insights into both its theoretical foundations and practical implementationsDiscusses generative AI models, unraveling the contrasts between machine learning, deep learning, and generative AIPresents AIbased models for the detection and generation of fraudulent contentCovers topics such as speech generation, deepfake technology, pose synthesis for animation, and sports performance analysisThis book is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology. The text showcases the use of designing artificial intelligence-based models for the detection and generation of misleading information using generative artificial intelligence. It covers topics such as neural machine translation, multilingual text generation, blog post generation, and social media post-synthesis. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Bibliographic Details

Title: Generative Artificial Intelligence (Hardcover)
Publisher: Taylor & Francis Ltd, London
Publication Date: 2025
Language: English
ISBN 10: 1032931647
ISBN 13: 9781032931647
Binding: Hardcover
Condition: new

About this title

Synopsis

This book comprehensively covers designing and implementing misinformation intervention strategies and risk communication approaches for generative artificial intelligence (AI) technologies.

Key Features:

Showcases cutting‑edge technology and offers insights into one of the most rapidly evolving fields in AI
Provides a comprehensive understanding of the underlying principles, algorithms, and applications of this cutting‑edge technology, offering insights into both its theoretical foundations and practical implementations
Discusses generative AI models, unraveling the contrasts between machine learning, deep learning, and generative AI
Presents AI‑based models for the detection and generation of fraudulent content
Covers topics such as speech generation, deepfake technology, pose synthesis for animation, and sports performance analysis

This book is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

About the Author

Dr. Deepika Varshney has been working as an Assistant Professor and serving academics and research in the Department of Computer Science and Engineering & Information Technology, Jaypee Institute of Information Technology, Noida, UP, since 2022. During her research career at Delhi Technological University, New Delhi, since 2019, she has worked on the cutting‑edge issue on social web platforms, specifically fraudulent content detection on social media platforms, and has received commendable research award of 50,000 for publishing article in SCI‑indexed journals in 2020, 2022, 2023, and 2024. She was also awarded with Senior Research Fellowship (SRF). She has published 20 research papers in SCI, SCOPUS, and international conferences. She has supervised both major and minor projects and is presently guiding two Ph.D. scholars. In addition, she has been actively involved in organizing short‑term training programs, faculty development programs (FDPs), and various academic initiatives. She also serves as a reviewer for several prestigious SCI‑indexed journals.

Dr. Preeti Nagrath is working as an Associate Professor at Bharati Vidyapeeth’s College of Engineering. She has more than 20 years of academic experience. She holds a B.Tech, an M.Tech, and a Ph.D. in Computer Science and Engineering. Her areas of research include network security, delay tolerant networks, machine learning, and deep learning. She is a member of ISTE. She has more than 60 research papers in SCI‑indexed journals, highly reputed journals, and international conferences. She has worked on a government‑funded DST project on women security. She has chaired many sessions at international conferences. She is appointed as a reviewer for many conferences and journals. She has organized many faculty development programs, workshops, hackathons, and guest lectures. She has mentored teams in Smart India Hackathons. She has worked as an Associate Editor for the Journal of Multidisciplinary Engineering Technologies at Bharati Vidyapeeth’s College of Engineering in New Delhi. She is currently teaching deep learning and machine learning, web engineering, network security, software testing, and object‑oriented software engineering.

Dr. Srishti Vashishtha is currently working at Bharati Vidyapeeth’s College of Engineering (BVCOE), GGSIPU, as an Assistant Professor in the Department of Computer Science and Engineering. She has received her Ph.D. degree in Sentiment Analysis and Social Media domain from Delhi Technological University in 2022. She has received a B.Tech degree in Information Technology from the Maharaja Surajmal Institute of Technology, GGSIPU, New Delhi, India, and an M.Tech degree in Computer Science from the University School of Information, Communication and Technology, GGSIPU. Her current areas of interest include machine learning, deep learning, data mining, natural language processing, sentiment analysis, speech emotion recognition, and fuzzy logic. She has about 10+ years of teaching experience in esteemed institutions. She qualified GATE and UGC‑NET. She has published 26 research papers in peer‑reviewed/Scopus/Web of Science‑indexed international journals and international conferences. She, with a current h‑index of 11, has published three Scopus‑indexed and six SCIE journal papers. She has published a book entitled Metaverse Technologies in Healthcare and holds two Indian design patents. She is a reviewer for various SCIE and peer‑reviewed journals. She has received DTU Research Excellence awards for commendable research (four times) in 2020, 2021, 2022, and 2023. She has received three Best Researcher awards from BVCOE in 2023 and 2024. She has received the Researcher of the Year award at the Universal Innovators Leadership Awards (UILA) organized by ICICC in 2024.

Victor Hugo C. de Albuquerque (Senior Member of IEEE) is currently a Professor and Senior Researcher at the Department of Teleinformatics Engineering (DETI)/Graduate Program in Teleinformatics Engineering (PPGETI) at the Federal University of Cear� (UFC), Brazil. He earned a Ph.D. in Mechanical Engineering from the Federal University of Para�ba (UFPB, 2010) and an M.Sc. in Teleinformatics Engineering from the PPGETI/UFC (UFC, 2007). He completed a BSE in Mechatronics Engineering at the Federal Center of Technological Education of Cear� (CEFETCE, 2006). He has experience in biomedical science and engineering, mainly in the research fields of applied computing, intelligent systems, visualization and interaction, with specific interest in pattern recognition, artificial intelligence, image processing and analysis, as well as automation with respect to biological signal/image processing, biomedical circuits, and human/brain–machine interaction, including augmented and virtual reality simulation modeling for animals and humans. He is a Full Member of the Brazilian Society of Biomedical Engineering (SBEB). He is an Editor‑in‑Chief of the Journal of Biomedical and Biological Sciences, as well as the Journal of Artificial Intelligence and Systems and the Journal of Biological Sciences, and an Associate Editor of the IEEE Journal of Biomedical and Health Informatics, Computers in Biology and Medicine, Frontiers in Cardiovascular Medicine, Computational Physiology and Medicine, Applied Soft Computing, IEEE Access, Frontiers in Communications and Networks, Computational Intelligence and Neuroscience, Measurement, and IET Quantum Communication. He has been a Lead Guest Editor of several highly reputed journals and a TPC member of many international conferences.

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