The book comprehensively covers designing and implementing misinformation intervention strategies and risk communication approaches for generative artificial intelligence technologies.
The text 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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Dr. Deepika Varshney is working as an Assistant Professor and serving academics & research in the Department of Computer Science and Engineering & Information Technology, Jaypee Institute of Information Technology, Noida-62, U.P., since 2022. During her research career in Delhi Technological University (New Delhi) since 2019, she worked on the cutting edge issue on social web platforms, Fraudulent Content detection on social media platforms and received commendable research award for publishing article in SCI indexed journals in the year of 2020, 2022, 2023 and 24 of amount 50,000. 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 PhD 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 in Bharati Vidyapeeth's College of Engineering. She has more than 20 years of Academic Experience. She is B.Tech (Computer Science and Engineering), M.Tech (Computer Science and Engineering) and PhD (Computer Science and Engineering). Her areas of research are network security, delay tolerant networks, machine learning and deep learning. She is the member of ISTE. She has more than 60 research papers in SCI- indexed journals, high reputed journals and international conferences. She has worked on Government funded DST project on Women security. She has chaired many sessions in international conferences. She is appointed as a reviewer in 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 ihas worked as Associate Editor of Journal of Multi-Disciplinary Engineering Technologies, Bharati Vidyapeeth's College of Engineering, and New Delhi. Currently teaching Deep learning and machine learning, Web Engineering, Network security, Software testing, 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 the B.Tech. degree in information technology from the Maharaja Surajmal Institute of Technology, GGSIPU, New Delhi, India, and the M.Tech. degree in Computer Science from the University School of Information, Communication and Technology, GGSIPU. Her current area of interest includes 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. Qualified GATE and UGC-NET. Published 26 research papers in Peer-reviewed/ Scopus/Web of Science indexed international journals and international conferences. Dr. Srishti, with a current h-index: of 11, has published 3 Scopus indexed and 6 SCIE journal papers. She has published book entitled "Metaverse Technologies in Healthcare" and 2 Indian design patents. She is a reviewer in various SCIE and Peer-reviewed journals. Dr. Srishti has received DTU Research Excellence awards for commendable research (four times) in the years 2020, 2021, 2022 and 2023. She has received 3 Best Researcher awards at BVCOE in 2023 and 2024. She has received Researcher of the year award at 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 Ceará (UFC), Brazil. He earned a Ph.D in Mechanical Engineering from the Federal University of Paraíba (UFPB, 2010), a MSc in Teleinformatics Engineering from the PPGETI/UFC (UFC, 2007). He completed a BSE in Mechatronics Engineering at the Federal Center of Technological Education of Ceará (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. Prof. Victor is a Full Member of the Brazilian Society of Biomedical Engineering (SBEB). He is Editor-in-Chief of the Journal of Biomedical and Biological Sciences, and, also, of the Journal of Artificial Intelligence and Systems, and Journal of Biological Sciences, as well as 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, IET Quantum Communication, and he has been Lead Guest Editor of several high-reputed journals, and TPC member of many international conferences.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardcover. Etat : new. 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 multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781032931647
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Hardcover. Etat : new. 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. N° de réf. du vendeur 9781032931647
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