Artículos de revistas sobre el tema "DETECTING DEEPFAKES"
Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros
Consulte los 50 mejores artículos de revistas para su investigación sobre el tema "DETECTING DEEPFAKES".
Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.
También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.
Explore artículos de revistas sobre una amplia variedad de disciplinas y organice su bibliografía correctamente.
Mai, Kimberly T., Sergi Bray, Toby Davies y Lewis D. Griffin. "Warning: Humans cannot reliably detect speech deepfakes". PLOS ONE 18, n.º 8 (2 de agosto de 2023): e0285333. http://dx.doi.org/10.1371/journal.pone.0285333.
Texto completoDobber, Tom, Nadia Metoui, Damian Trilling, Natali Helberger y Claes de Vreese. "Do (Microtargeted) Deepfakes Have Real Effects on Political Attitudes?" International Journal of Press/Politics 26, n.º 1 (25 de julio de 2020): 69–91. http://dx.doi.org/10.1177/1940161220944364.
Texto completoVinogradova, Ekaterina. "The malicious use of political deepfakes and attempts to neutralize them in Latin America". Latinskaia Amerika, n.º 5 (2023): 35. http://dx.doi.org/10.31857/s0044748x0025404-3.
Texto completoSingh, Preeti, Khyati Chaudhary, Gopal Chaudhary, Manju Khari y Bharat Rawal. "A Machine Learning Approach to Detecting Deepfake Videos: An Investigation of Feature Extraction Techniques". Journal of Cybersecurity and Information Management 9, n.º 2 (2022): 42–50. http://dx.doi.org/10.54216/jcim.090204.
Texto completoDas, Rashmiranjan, Gaurav Negi y Alan F. Smeaton. "Detecting Deepfake Videos Using Euler Video Magnification". Electronic Imaging 2021, n.º 4 (18 de enero de 2021): 272–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.4.mwsf-272.
Texto completoRaza, Ali, Kashif Munir y Mubarak Almutairi. "A Novel Deep Learning Approach for Deepfake Image Detection". Applied Sciences 12, n.º 19 (29 de septiembre de 2022): 9820. http://dx.doi.org/10.3390/app12199820.
Texto completoJameel, Wildan J., Suhad M. Kadhem y Ayad R. Abbas. "Detecting Deepfakes with Deep Learning and Gabor Filters". ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY 10, n.º 1 (18 de marzo de 2022): 18–22. http://dx.doi.org/10.14500/aro.10917.
Texto completoGiudice, Oliver, Luca Guarnera y Sebastiano Battiato. "Fighting Deepfakes by Detecting GAN DCT Anomalies". Journal of Imaging 7, n.º 8 (30 de julio de 2021): 128. http://dx.doi.org/10.3390/jimaging7080128.
Texto completoLim, Suk-Young, Dong-Kyu Chae y Sang-Chul Lee. "Detecting Deepfake Voice Using Explainable Deep Learning Techniques". Applied Sciences 12, n.º 8 (13 de abril de 2022): 3926. http://dx.doi.org/10.3390/app12083926.
Texto completoGadgilwar, Jitesh, Kunal Rahangdale, Om Jaiswal, Parag Asare, Pratik Adekar y Prof Leela Bitla. "Exploring Deepfakes - Creation Techniques, Detection Strategies, and Emerging Challenges: A Survey". International Journal for Research in Applied Science and Engineering Technology 11, n.º 3 (31 de marzo de 2023): 1491–95. http://dx.doi.org/10.22214/ijraset.2023.49681.
Texto completoDobrobaba, M. B. "Deepfakes as a Threat to Human Rights". Lex Russica 75, n.º 11 (14 de noviembre de 2022): 112–19. http://dx.doi.org/10.17803/1729-5920.2022.192.11.112-119.
Texto completoSalvi, Davide, Honggu Liu, Sara Mandelli, Paolo Bestagini, Wenbo Zhou, Weiming Zhang y Stefano Tubaro. "A Robust Approach to Multimodal Deepfake Detection". Journal of Imaging 9, n.º 6 (19 de junio de 2023): 122. http://dx.doi.org/10.3390/jimaging9060122.
Texto completoTursman, Eleanor. "Detecting deepfakes using crowd consensus". XRDS: Crossroads, The ACM Magazine for Students 27, n.º 1 (4 de septiembre de 2020): 22–25. http://dx.doi.org/10.1145/3416061.
Texto completoMateen, Marium y Narmeen Zakaria Bawany. "Deep Learning Approach for Detecting Audio Deepfakes in Urdu". NUML International Journal of Engineering and Computing 2, n.º 1 (26 de julio de 2023): 1–11. http://dx.doi.org/10.52015/nijec.v2i1.37.
Texto completoChoi, Nakhoon y Heeyoul Kim. "DDS: Deepfake Detection System through Collective Intelligence and Deep-Learning Model in Blockchain Environment". Applied Sciences 13, n.º 4 (7 de febrero de 2023): 2122. http://dx.doi.org/10.3390/app13042122.
Texto completoWan, Da, Manchun Cai, Shufan Peng, Wenkai Qin y Lanting Li. "Deepfake Detection Algorithm Based on Dual-Branch Data Augmentation and Modified Attention Mechanism". Applied Sciences 13, n.º 14 (18 de julio de 2023): 8313. http://dx.doi.org/10.3390/app13148313.
Texto completoFrick, Raphael Antonius, Sascha Zmudzinski y Martin Steinebach. "Detecting Deepfakes with Haralick’s Texture Properties". Electronic Imaging 2021, n.º 4 (18 de enero de 2021): 271–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.4.mwsf-271.
Texto completoTaeb, Maryam y Hongmei Chi. "Comparison of Deepfake Detection Techniques through Deep Learning". Journal of Cybersecurity and Privacy 2, n.º 1 (4 de marzo de 2022): 89–106. http://dx.doi.org/10.3390/jcp2010007.
Texto completoAmatika, Faith. "The Regulation of Deepfakes in Kenya". Journal of Intellectual Property and Information Technology Law (JIPIT) 2, n.º 1 (15 de septiembre de 2022): 145–86. http://dx.doi.org/10.52907/jipit.v2i1.208.
Texto completoArshed, Muhammad Asad, Ayed Alwadain, Rao Faizan Ali, Shahzad Mumtaz, Muhammad Ibrahim y Amgad Muneer. "Unmasking Deception: Empowering Deepfake Detection with Vision Transformer Network". Mathematics 11, n.º 17 (29 de agosto de 2023): 3710. http://dx.doi.org/10.3390/math11173710.
Texto completoYasrab, Robail, Wanqi Jiang y Adnan Riaz. "Fighting Deepfakes Using Body Language Analysis". Forecasting 3, n.º 2 (28 de abril de 2021): 303–21. http://dx.doi.org/10.3390/forecast3020020.
Texto completoTran, Van-Nhan, Suk-Hwan Lee, Hoanh-Su Le y Ki-Ryong Kwon. "High Performance DeepFake Video Detection on CNN-Based with Attention Target-Specific Regions and Manual Distillation Extraction". Applied Sciences 11, n.º 16 (20 de agosto de 2021): 7678. http://dx.doi.org/10.3390/app11167678.
Texto completoLe, Vincent. "The Deepfakes to Come: A Turing Cop’s Nightmare". Identities: Journal for Politics, Gender and Culture 17, n.º 2-3 (30 de diciembre de 2020): 8–18. http://dx.doi.org/10.51151/identities.v17i2-3.468.
Texto completoFrick, Raphael Antonius, Sascha Zmudzinski y Martin Steinebach. "Detecting “DeepFakes” in H.264 Video Data Using Compression Ghost Artifacts". Electronic Imaging 2020, n.º 4 (26 de enero de 2020): 116–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.4.mwsf-116.
Texto completoSaxena, Akash, Dharmendra Yadav, Manish Gupta, Sunil Phulre, Tripti Arjariya, Varshali Jaiswal y Rakesh Kumar Bhujade. "Detecting Deepfakes: A Novel Framework Employing XceptionNet-Based Convolutional Neural Networks". Traitement du Signal 40, n.º 3 (28 de junio de 2023): 835–46. http://dx.doi.org/10.18280/ts.400301.
Texto completoA. Abu-Ein, Ashraf, Obaida M. Al-Hazaimeh, Alaa M. Dawood y Andraws I. Swidan. "Analysis of the current state of deepfake techniques-creation and detection methods". Indonesian Journal of Electrical Engineering and Computer Science 28, n.º 3 (7 de octubre de 2022): 1659. http://dx.doi.org/10.11591/ijeecs.v28.i3.pp1659-1667.
Texto completoGodulla, Alexander, Christian P. Hoffmann y Daniel Seibert. "Dealing with deepfakes – an interdisciplinary examination of the state of research and implications for communication studies". Studies in Communication and Media 10, n.º 1 (2021): 72–96. http://dx.doi.org/10.5771/2192-4007-2021-1-72.
Texto completoShahzad, Hina Fatima, Furqan Rustam, Emmanuel Soriano Flores, Juan Luís Vidal Mazón, Isabel de la Torre Diez y Imran Ashraf. "A Review of Image Processing Techniques for Deepfakes". Sensors 22, n.º 12 (16 de junio de 2022): 4556. http://dx.doi.org/10.3390/s22124556.
Texto completoVinay, A., Paras S. Khurana, T. B. Sudarshan, S. Natarajan, Vivek Nagesh, Vishruth Lakshminarayanan y Niput Bhat. "AFMB-Net". Tehnički glasnik 16, n.º 4 (26 de septiembre de 2022): 503–8. http://dx.doi.org/10.31803/tg-20220403080215.
Texto completoJiang, Jianguo, Boquan Li, Baole Wei, Gang Li, Chao Liu, Weiqing Huang, Meimei Li y Min Yu. "FakeFilter: A cross-distribution Deepfake detection system with domain adaptation". Journal of Computer Security 29, n.º 4 (18 de junio de 2021): 403–21. http://dx.doi.org/10.3233/jcs-200124.
Texto completoGuarnera, Luca, Oliver Giudice, Francesco Guarnera, Alessandro Ortis, Giovanni Puglisi, Antonino Paratore, Linh M. Q. Bui et al. "The Face Deepfake Detection Challenge". Journal of Imaging 8, n.º 10 (28 de septiembre de 2022): 263. http://dx.doi.org/10.3390/jimaging8100263.
Texto completoLópez-Gil, Juan-Miguel, Rosa Gil y Roberto García. "Do Deepfakes Adequately Display Emotions? A Study on Deepfake Facial Emotion Expression". Computational Intelligence and Neuroscience 2022 (18 de octubre de 2022): 1–12. http://dx.doi.org/10.1155/2022/1332122.
Texto completoKhormali, Aminollah y Jiann-Shiun Yuan. "ADD: Attention-Based DeepFake Detection Approach". Big Data and Cognitive Computing 5, n.º 4 (27 de septiembre de 2021): 49. http://dx.doi.org/10.3390/bdcc5040049.
Texto completoShad, Hasin Shahed, Md Mashfiq Rizvee, Nishat Tasnim Roza, S. M. Ahsanul Hoq, Mohammad Monirujjaman Khan, Arjun Singh, Atef Zaguia y Sami Bourouis. "Comparative Analysis of Deepfake Image Detection Method Using Convolutional Neural Network". Computational Intelligence and Neuroscience 2021 (16 de diciembre de 2021): 1–18. http://dx.doi.org/10.1155/2021/3111676.
Texto completoNoreen, Iram, Muhammad Shahid Muneer y Saira Gillani. "Deepfake attack prevention using steganography GANs". PeerJ Computer Science 8 (20 de octubre de 2022): e1125. http://dx.doi.org/10.7717/peerj-cs.1125.
Texto completoBogdanova, D. A. "About some aspects of digital ecology". Informatics in school, n.º 7 (19 de noviembre de 2021): 15–19. http://dx.doi.org/10.32517/2221-1993-2021-20-7-15-19.
Texto completoAkhtar, Zahid. "Deepfakes Generation and Detection: A Short Survey". Journal of Imaging 9, n.º 1 (13 de enero de 2023): 18. http://dx.doi.org/10.3390/jimaging9010018.
Texto completoCoccomini, Davide Alessandro, Roberto Caldelli, Fabrizio Falchi y Claudio Gennaro. "On the Generalization of Deep Learning Models in Video Deepfake Detection". Journal of Imaging 9, n.º 5 (29 de abril de 2023): 89. http://dx.doi.org/10.3390/jimaging9050089.
Texto completoOlariu, Oana. "Critical Thinking as Dynamic Shield against Media Deception. Exploring Connections between the Analytical Mind and Detecting Disinformation Techniques and Logical Fallacies in Journalistic Production". Logos Universality Mentality Education Novelty: Social Sciences 11, n.º 1 (2 de septiembre de 2022): 29–57. http://dx.doi.org/10.18662/lumenss/11.1/61.
Texto completoMaharjan, Ashish y Asish Shakya. "Learning Approaches used by Different Applications to Achieve Deep Fake Technology". Interdisciplinary Journal of Innovation in Nepalese Academia 2, n.º 1 (22 de junio de 2023): 96–101. http://dx.doi.org/10.3126/idjina.v2i1.55969.
Texto completoLee, Gihun y Mihui Kim. "Deepfake Detection Using the Rate of Change between Frames Based on Computer Vision". Sensors 21, n.º 21 (5 de noviembre de 2021): 7367. http://dx.doi.org/10.3390/s21217367.
Texto completoKale, Prachi. "Forensic Verification and Detection of Fake Video using Deep Fake Algorithm". International Journal for Research in Applied Science and Engineering Technology 9, n.º VI (30 de junio de 2021): 2789–94. http://dx.doi.org/10.22214/ijraset.2021.35599.
Texto completoKhormali, Aminollah y Jiann-Shiun Yuan. "DFDT: An End-to-End DeepFake Detection Framework Using Vision Transformer". Applied Sciences 12, n.º 6 (14 de marzo de 2022): 2953. http://dx.doi.org/10.3390/app12062953.
Texto completoMehra, Aman, Akshay Agarwal, Mayank Vatsa y Richa Singh. "Detection of Digital Manipulation in Facial Images (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 18 (18 de mayo de 2021): 15845–46. http://dx.doi.org/10.1609/aaai.v35i18.17919.
Texto completoYavuzkilic, Semih, Abdulkadir Sengur, Zahid Akhtar y Kamran Siddique. "Spotting Deepfakes and Face Manipulations by Fusing Features from Multi-Stream CNNs Models". Symmetry 13, n.º 8 (26 de julio de 2021): 1352. http://dx.doi.org/10.3390/sym13081352.
Texto completoBalasubramanian, Saravana Balaji, Jagadeesh Kannan R, Prabu P, Venkatachalam K y Pavel Trojovský. "Deep fake detection using cascaded deep sparse auto-encoder for effective feature selection". PeerJ Computer Science 8 (13 de julio de 2022): e1040. http://dx.doi.org/10.7717/peerj-cs.1040.
Texto completoYang, Sung-Hyun, Keshav Thapa y Barsha Lamichhane. "Detection of Image Level Forgery with Various Constraints Using DFDC Full and Sample Datasets". Sensors 22, n.º 23 (24 de noviembre de 2022): 9121. http://dx.doi.org/10.3390/s22239121.
Texto completoAmoah-Yeboah, Yaw. "Biometric Spoofing and Deepfake Detection". Advances in Multidisciplinary and scientific Research Journal Publication 1, n.º 1 (26 de julio de 2022): 279–84. http://dx.doi.org/10.22624/aims/crp-bk3-p45.
Texto completoĐorđević, Miljan, Milan Milivojević y Ana Gavrovska. "DeepFake video production and SIFT-based analysis". Telfor Journal 12, n.º 1 (2020): 22–27. http://dx.doi.org/10.5937/telfor2001022q.
Texto completoBinh, Le Minh y Simon Woo. "ADD: Frequency Attention and Multi-View Based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 1 (28 de junio de 2022): 122–30. http://dx.doi.org/10.1609/aaai.v36i1.19886.
Texto completo