Artículos de revistas sobre el tema "FAKE VIDEOS"
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Abidin, Muhammad Indra, Ingrid Nurtanio y Andani Achmad. "Deepfake Detection in Videos Using Long Short-Term Memory and CNN ResNext". ILKOM Jurnal Ilmiah 14, n.º 3 (19 de diciembre de 2022): 178–85. http://dx.doi.org/10.33096/ilkom.v14i3.1254.178-185.
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 completoArunkumar, P. M., Yalamanchili Sangeetha, P. Vishnu Raja y S. N. Sangeetha. "Deep Learning for Forgery Face Detection Using Fuzzy Fisher Capsule Dual Graph". Information Technology and Control 51, n.º 3 (23 de septiembre de 2022): 563–74. http://dx.doi.org/10.5755/j01.itc.51.3.31510.
Texto completoWang, Shuting (Ada), Min-Seok Pang y Paul Pavlou. "Seeing Is Believing? How Including a Video in Fake News Influences Users’ Reporting of Fake News to Social Media Platforms". MIS Quarterly 45, n.º 3 (1 de septiembre de 2022): 1323–54. http://dx.doi.org/10.25300/misq/2022/16296.
Texto completoDeng, Liwei, Hongfei Suo y Dongjie Li. "Deepfake Video Detection Based on EfficientNet-V2 Network". Computational Intelligence and Neuroscience 2022 (15 de abril de 2022): 1–13. http://dx.doi.org/10.1155/2022/3441549.
Texto completoShahar, Hadas y Hagit Hel-Or. "Fake Video Detection Using Facial Color". Color and Imaging Conference 2020, n.º 28 (4 de noviembre de 2020): 175–80. http://dx.doi.org/10.2352/issn.2169-2629.2020.28.27.
Texto completoLin, Yih-Kai y Hao-Lun Sun. "Few-Shot Training GAN for Face Forgery Classification and Segmentation Based on the Fine-Tune Approach". Electronics 12, n.º 6 (16 de marzo de 2023): 1417. http://dx.doi.org/10.3390/electronics12061417.
Texto completoLiang, Xiaoyun, Zhaohong Li, Zhonghao Li y Zhenzhen Zhang. "Fake Bitrate Detection of HEVC Videos Based on Prediction Process". Symmetry 11, n.º 7 (15 de julio de 2019): 918. http://dx.doi.org/10.3390/sym11070918.
Texto completoPei, Pengfei, Xianfeng Zhao, Jinchuan Li, Yun Cao y Xuyuan Lai. "Vision Transformer-Based Video Hashing Retrieval for Tracing the Source of Fake Videos". Security and Communication Networks 2023 (28 de junio de 2023): 1–16. http://dx.doi.org/10.1155/2023/5349392.
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 completoMaras, Marie-Helen y Alex Alexandrou. "Determining authenticity of video evidence in the age of artificial intelligence and in the wake of Deepfake videos". International Journal of Evidence & Proof 23, n.º 3 (28 de octubre de 2018): 255–62. http://dx.doi.org/10.1177/1365712718807226.
Texto completoJin, Xinlei, Dengpan Ye y Chuanxi Chen. "Countering Spoof: Towards Detecting Deepfake with Multidimensional Biological Signals". Security and Communication Networks 2021 (22 de abril de 2021): 1–8. http://dx.doi.org/10.1155/2021/6626974.
Texto completoSanilM, Rithvika, S. Saathvik, Rithesh RaiK y Srinivas P M. "DEEPFAKE DETECTION USING EYE-BLINKING PATTERN". International Journal of Engineering Applied Sciences and Technology 7, n.º 3 (1 de julio de 2022): 229–34. http://dx.doi.org/10.33564/ijeast.2022.v07i03.036.
Texto completoAwotunde, Joseph Bamidele, Rasheed Gbenga Jimoh, Agbotiname Lucky Imoize, Akeem Tayo Abdulrazaq, Chun-Ta Li y Cheng-Chi Lee. "An Enhanced Deep Learning-Based DeepFake Video Detection and Classification System". Electronics 12, n.º 1 (26 de diciembre de 2022): 87. http://dx.doi.org/10.3390/electronics12010087.
Texto completoQi, Peng, Yuyan Bu, Juan Cao, Wei Ji, Ruihao Shui, Junbin Xiao, Danding Wang y Tat-Seng Chua. "FakeSV: A Multimodal Benchmark with Rich Social Context for Fake News Detection on Short Video Platforms". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 12 (26 de junio de 2023): 14444–52. http://dx.doi.org/10.1609/aaai.v37i12.26689.
Texto completoLai, Zhimao, Yufei Wang, Renhai Feng, Xianglei Hu y Haifeng Xu. "Multi-Feature Fusion Based Deepfake Face Forgery Video Detection". Systems 10, n.º 2 (7 de marzo de 2022): 31. http://dx.doi.org/10.3390/systems10020031.
Texto completoDoke, Yash. "Deep fake Detection Through Deep Learning". International Journal for Research in Applied Science and Engineering Technology 11, n.º 5 (31 de mayo de 2023): 861–66. http://dx.doi.org/10.22214/ijraset.2023.51630.
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 completoGarcía-Retuerta, David, Álvaro Bartolomé, Pablo Chamoso y Juan Manuel Corchado. "Counter-Terrorism Video Analysis Using Hash-Based Algorithms". Algorithms 12, n.º 5 (24 de mayo de 2019): 110. http://dx.doi.org/10.3390/a12050110.
Texto completoMegawan, Sunario, Wulan Sri Lestari y Apriyanto Halim. "Deteksi Non-Spoofing Wajah pada Video secara Real Time Menggunakan Faster R-CNN". Journal of Information System Research (JOSH) 3, n.º 3 (29 de abril de 2022): 291–99. http://dx.doi.org/10.47065/josh.v3i3.1519.
Texto completoFerreira, Sara, Mário Antunes y Manuel E. Correia. "Exposing Manipulated Photos and Videos in Digital Forensics Analysis". Journal of Imaging 7, n.º 7 (24 de junio de 2021): 102. http://dx.doi.org/10.3390/jimaging7070102.
Texto completoWu, Nan, Xin Jin, Qian Jiang, Puming Wang, Ya Zhang, Shaowen Yao y Wei Zhou. "Multisemantic Path Neural Network for Deepfake Detection". Security and Communication Networks 2022 (11 de octubre de 2022): 1–14. http://dx.doi.org/10.1155/2022/4976848.
Texto completoThaseen Ikram, Sumaiya, Priya V, Shourya Chambial, Dhruv Sood y Arulkumar V. "A Performance Enhancement of Deepfake Video Detection through the use of a Hybrid CNN Deep Learning Model". International journal of electrical and computer engineering systems 14, n.º 2 (27 de febrero de 2023): 169–78. http://dx.doi.org/10.32985/ijeces.14.2.6.
Texto completoAshish Ransom, Shashank Shekhar,. "Ethical & Legal Implications of Deep Fake Technology: A Global Overview". Proceeding International Conference on Science and Engineering 11, n.º 1 (18 de febrero de 2023): 2226–35. http://dx.doi.org/10.52783/cienceng.v11i1.398.
Texto completoSaealal, Muhammad Salihin, Mohd Zamri Ibrahim, David J. Mulvaney, Mohd Ibrahim Shapiai y Norasyikin Fadilah. "Using cascade CNN-LSTM-FCNs to identify AI-altered video based on eye state sequence". PLOS ONE 17, n.º 12 (15 de diciembre de 2022): e0278989. http://dx.doi.org/10.1371/journal.pone.0278989.
Texto completoHubálovský, Štěpán, Pavel Trojovský, Nebojsa Bacanin y Venkatachalam K. "Evaluation of deepfake detection using YOLO with local binary pattern histogram". PeerJ Computer Science 8 (13 de septiembre de 2022): e1086. http://dx.doi.org/10.7717/peerj-cs.1086.
Texto completoTambe, Swapnali, Anil Pawar y S. K. Yadav. "Deep fake videos identification using ANN and LSTM". Journal of Discrete Mathematical Sciences and Cryptography 24, n.º 8 (17 de noviembre de 2021): 2353–64. http://dx.doi.org/10.1080/09720529.2021.2014140.
Texto completoMuqsith, Munadhil Abdul y Rizky Ridho Pratomo. "The Development of Fake News in the Post-Truth Age". SALAM: Jurnal Sosial dan Budaya Syar-i 8, n.º 5 (22 de septiembre de 2021): 1391–406. http://dx.doi.org/10.15408/sjsbs.v8i5.22395.
Texto completoIsmail, Aya, Marwa Elpeltagy, Mervat S. Zaki y Kamal Eldahshan. "A New Deep Learning-Based Methodology for Video Deepfake Detection Using XGBoost". Sensors 21, n.º 16 (10 de agosto de 2021): 5413. http://dx.doi.org/10.3390/s21165413.
Texto completoIsmail, Aya, Marwa Elpeltagy, Mervat Zaki y Kamal A. ElDahshan. "Deepfake video detection: YOLO-Face convolution recurrent approach". PeerJ Computer Science 7 (21 de septiembre de 2021): e730. http://dx.doi.org/10.7717/peerj-cs.730.
Texto completoNassif, Ali Bou, Qassim Nasir, Manar Abu Talib y Omar Mohamed Gouda. "Improved Optical Flow Estimation Method for Deepfake Videos". Sensors 22, n.º 7 (24 de marzo de 2022): 2500. http://dx.doi.org/10.3390/s22072500.
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 completoSohaib, Muhammad y Samabia Tehseen. "Forgery detection of low quality deepfake videos". Neural Network World 33, n.º 2 (2023): 85–99. http://dx.doi.org/10.14311/nnw.2023.33.006.
Texto completoBansal, Nency, Turki Aljrees, Dhirendra Prasad Yadav, Kamred Udham Singh, Ankit Kumar, Gyanendra Kumar Verma y Teekam Singh. "Real-Time Advanced Computational Intelligence for Deep Fake Video Detection". Applied Sciences 13, n.º 5 (27 de febrero de 2023): 3095. http://dx.doi.org/10.3390/app13053095.
Texto completoSabah, Hanady. "Detection of Deep Fake in Face Images Using Deep Learning". Wasit Journal of Computer and Mathematics Science 1, n.º 4 (31 de diciembre de 2022): 94–111. http://dx.doi.org/10.31185/wjcm.92.
Texto completoBilohrats, Khrystyna. "PECULIARITIES OF FAKE MEDIA MESSAGES (ON THE EXAMPLE OF RUSSIAN FAKES ABOUT UKRAINE)". Bulletin of Lviv Polytechnic National University: journalism 1, n.º 2 (2021): 1–10. http://dx.doi.org/10.23939/sjs2021.02.001.
Texto completoShalini, S. "Fake Image Detection". International Journal for Research in Applied Science and Engineering Technology 9, n.º VI (15 de junio de 2021): 1140–45. http://dx.doi.org/10.22214/ijraset.2021.35238.
Texto completoDutta, Hridoy Sankar, Mayank Jobanputra, Himani Negi y Tanmoy Chakraborty. "Detecting and Analyzing Collusive Entities on YouTube". ACM Transactions on Intelligent Systems and Technology 12, n.º 5 (31 de octubre de 2021): 1–28. http://dx.doi.org/10.1145/3477300.
Texto completoShan Bian, Weiqi Luo y Jiwu Huang. "Exposing Fake Bit Rate Videos and Estimating Original Bit Rates". IEEE Transactions on Circuits and Systems for Video Technology 24, n.º 12 (diciembre de 2014): 2144–54. http://dx.doi.org/10.1109/tcsvt.2014.2334031.
Texto completoLiang, Xiaoyun, Zhaohong Li, Yiyuan Yang, Zhenzhen Zhang y Yu Zhang. "Detection of Double Compression for HEVC Videos With Fake Bitrate". IEEE Access 6 (2018): 53243–53. http://dx.doi.org/10.1109/access.2018.2869627.
Texto completoAlsakar, Yasmin M., Nagham E. Mekky y Noha A. Hikal. "Detecting and Locating Passive Video Forgery Based on Low Computational Complexity Third-Order Tensor Representation". Journal of Imaging 7, n.º 3 (5 de marzo de 2021): 47. http://dx.doi.org/10.3390/jimaging7030047.
Texto completoBurgstaller, Markus y Scott Macpherson. "Deepfakes in International Arbitration: How Should Tribunals Treat Video Evidence and Allegations of Technological Tampering?" Journal of World Investment & Trade 22, n.º 5-6 (10 de diciembre de 2021): 860–90. http://dx.doi.org/10.1163/22119000-12340232.
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 completoWagner, Travis L. y Ashley Blewer. "“The Word Real Is No Longer Real”: Deepfakes, Gender, and the Challenges of AI-Altered Video". Open Information Science 3, n.º 1 (1 de enero de 2019): 32–46. http://dx.doi.org/10.1515/opis-2019-0003.
Texto completoPérez Dasilva, Jesús, Koldobika Meso Ayerdi y Terese Mendiguren Galdospin. "Deepfakes on Twitter: Which Actors Control Their Spread?" Media and Communication 9, n.º 1 (3 de marzo de 2021): 301–12. http://dx.doi.org/10.17645/mac.v9i1.3433.
Texto completoAdams, Caitlin. "“It’s So Bad It Has to be Real”: Mimic Vlogs and the Use of User-Generated Formats for Storytelling". Platform: Journal of Media and Communication 9, n.º 2 (diciembre de 2022): 22–36. http://dx.doi.org/10.46580/p84398.
Texto completoAn, Byeongseon, Hyeji Lim y Eui Chul Lee. "Fake Biometric Detection Based on Photoplethysmography Extracted from Short Hand Videos". Electronics 12, n.º 17 (26 de agosto de 2023): 3605. http://dx.doi.org/10.3390/electronics12173605.
Texto completoS., Gayathri, Santhiya S., Nowneesh T., Sanjana Shuruthy K. y Sakthi S. "Deep fake detection using deep learning techniques". Applied and Computational Engineering 2, n.º 1 (22 de marzo de 2023): 1010–19. http://dx.doi.org/10.54254/2755-2721/2/20220655.
Texto completoClaretta, Dyva y Marta Wijayanengtias. "VIEWER RECEPTION TOWARD YOUTUBER'S GIVEAWAY". JOSAR (Journal of Students Academic Research) 7, n.º 1 (22 de mayo de 2021): 45–57. http://dx.doi.org/10.35457/josar.v7i1.1533.
Texto completoRupapara, Vaibhav, Furqan Rustam, Aashir Amaar, Patrick Bernard Washington, Ernesto Lee y Imran Ashraf. "Deepfake tweets classification using stacked Bi-LSTM and words embedding". PeerJ Computer Science 7 (21 de octubre de 2021): e745. http://dx.doi.org/10.7717/peerj-cs.745.
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