Zobrazeno 1 - 8
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pro vyhledávání: '"Se Rim Park"'
Publikováno v:
Journal of Sport and Leisure Studies. 85:93-103
Publikováno v:
EMNLP (1)
We present our HABERTOR model for detecting hatespeech in large scale user-generated content. Inspired by the recent success of the BERT model, we propose several modifications to BERT to enhance the performance on the downstream hatespeech classific
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0fac964e8d7c98e6e3ee5aed1809c1f7
http://arxiv.org/abs/2010.08865
http://arxiv.org/abs/2010.08865
Publikováno v:
Food and Life.
Publikováno v:
IEEE Transactions on Image Processing. 25:920-934
Invertible image representation methods (transforms) are routinely employed as low-level image processing operations based on which feature extraction and recognition algorithms are developed. Most transforms in current use (e.g., Fourier, wavelet, a
Publikováno v:
Kolouri, S, Park, S, Thorpe, M, Rohde, G & Slepcev, D 2017, ' Optimal Mass Transport: Signal processing and machine-learning applications ', IEEE Signal Processing Magazine, vol. 34, no. 4, pp. 43-59 . https://doi.org/10.1109/MSP.2017.2695801
Transport-based techniques for signal and data analysis have received increased attention recently. Given their ability to provide accurate generative models for signal intensities and other data distributions, they have been used in a variety of app
Autor:
Se Rim Park, Gustavo K. Rohde, Timothy Doster, Jonathan M. Nichols, Liam Cattell, Abbie T. Watnik
Publikováno v:
Optics express. 26(4)
Free space optical communications utilizing orbital angular momentum beams have recently emerged as a new technique for communications with potential for increased channel capacity. Turbulence due to changes in the index of refraction emanating from
Autor:
Se Rim Park, Jinwon Lee
Publikováno v:
INTERSPEECH
In hearing aids, the presence of babble noise degrades hearing intelligibility of human speech greatly. However, removing the babble without creating artifacts in human speech is a challenging task in a low SNR environment. Here, we sought to solve t
Discriminating data classes emanating from sensors is an important problem with many applications in science and technology. We describe a new transform for pattern representation that interprets patterns as probability density functions, and has spe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17bf447ca06df625616337cf48b2edfe