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pro vyhledávání: '"Mascarenhas, Royston"'
Autor:
Mahalingam, Anand Gokul, Shah, Aayush, Gulati, Akshay, Mascarenhas, Royston, Panduranga, Rakshitha
Improving performance in multiple domains is a challenging task, and often requires significant amounts of data to train and test models. Active learning techniques provide a promising solution by enabling models to select the most informative sample
Externí odkaz:
http://arxiv.org/abs/2304.06277
Autor:
Masi, Iacopo, Killekar, Aditya, Mascarenhas, Royston Marian, Gurudatt, Shenoy Pratik, AbdAlmageed, Wael
The current spike of hyper-realistic faces artificially generated using deepfakes calls for media forensics solutions that are tailored to video streams and work reliably with a low false alarm rate at the video level. We present a method for deepfak
Externí odkaz:
http://arxiv.org/abs/2008.03412
Autor:
Amaral, Alexandro Da Silva, Sjoden, Glen E., Crommelin, G.A.K., Mercier, Gil A., Tuominen, Pekka, Khan, Mustayeen A., Goel, Abhinav, Mascarenhas, Royston, Tran, Pierre, Radtke, Werner, Beltramo, Michael N., Cason, Todd J., Taylor, Michael, Jegathesan, J., Chua, Wee Beng, Ohazama, Toshitaka, De Mattos, Cristiano Tavares, Pagac, Karl H., Haas, Daniel
Publikováno v:
Newsweek (Pacific Edition); 11/15/99 (Pacific Edition), Vol. 134 Issue 20, p7, 3p
