Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Sakthi Balan Muthiah"'
Autor:
Arpan Gupta, Sakthi Balan Muthiah
Publikováno v:
Multimedia Tools and Applications. 82:1237-1259
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78ef5af9364cc5e5889c405b652cede7
https://doi.org/10.1007/s11042-022-13307-y
https://doi.org/10.1007/s11042-022-13307-y
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1cd58f4cbf8142314cc47d2b3eb96180
https://doi.org/10.2139/ssrn.4251024
https://doi.org/10.2139/ssrn.4251024
Autor:
Nishanth Sastry, Pushkal Agarwal, Sakthi Balan Muthiah, Nicolas Kourtellis, Sangeeta Mahapatra, Yash Vekaria, Vibhor Agarwal
Publikováno v:
13th ACM Web Science Conference 2021
WebSci
WebSci
Online user privacy and tracking have been extensively studied in recent years, especially due to privacy and personal data-related legislations in the EU and the USA, such as the General Data Protection Regulation, ePrivacy Regulation, and Californi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::221ed6c38cab2daa85e5e04c807bdb73
https://zenodo.org/record/7925689
https://zenodo.org/record/7925689
Publikováno v:
WebSci (Companion)
Detecting events from social media data is an important problem. In this paper, we propose a method to detect events by looking at a novel parameter – the average number of common friends of all the pairs of users present in the dataset. This is a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4bacd91bdc6de76bbac21813598c8ff7
https://doi.org/10.1145/3462741.3466654
https://doi.org/10.1145/3462741.3466654
Publikováno v:
Proceedings of the Fifteenth International AAAI Conference on Web and Social Media(ICWSM 2021)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=r3c4b2081b22::17a400b885d3a16dc14b567806f5ff0e
Publikováno v:
Research Challenges in Information Science ISBN: 9783030750176
RCIS
RCIS
Detecting events from social media data is an important problem. In this paper, we propose a novel method to detect events by detecting traces of herding in the Twitter data. We analyze only the metadata for this and not the content of the tweets. We
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::49437ccf0cd9b109cfb9ae71e05e853d
https://doi.org/10.1007/978-3-030-75018-3_47
https://doi.org/10.1007/978-3-030-75018-3_47
Publikováno v:
Communications in Computer and Information Science ISBN: 9789811610912
CVIP (2)
CVIP (2)
In this work, we deal with the problem of activity recognition in Cricket telecast videos. We present a supervised approach for recognizing Cricket stroke categories using two variants of Bag of Visual words (BoV) model applied on dense optical flow
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca58b42f3ce117d1fd508263b90969fe
https://doi.org/10.1007/978-981-16-1092-9_20
https://doi.org/10.1007/978-981-16-1092-9_20
Publikováno v:
WI/IAT
Online communication is fast becoming an integral part of how our society functions. As a result, studying the patterns of online collective behaviors – especially over online social networks – is important. This work has two parts firstly, redef
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eee5ef12b42e4f461d5c379014cc0c51
https://doi.org/10.1109/wiiat50758.2020.00067
https://doi.org/10.1109/wiiat50758.2020.00067
Publikováno v:
WebSci
For more than three years, Google has been facilitating users with four gender options ??Male", ?Female", ?Rather Not Say" and ?Custom". ?Rather Not Say" is for users who do not prefer to disclose their gender identity and ?Custom" is for users who d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3bb5ad843500cbfacb6c29e1ea729f70
https://doi.org/10.1145/3292522.3326033
https://doi.org/10.1145/3292522.3326033
Autor:
Arpan Gupta, Sakthi Balan Muthiah
Publikováno v:
Image and Vision Computing. 100:103944
In this work, we create two new video datasets for the task of temporal Cricket stroke extraction. The two datasets, namely, the Highlights dataset (with approx. 117K frames) and the Generic dataset (with approx. 1.93M frames), comprise of Cricket te
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d61a5634bc0089ab605f006f4e9e120
https://doi.org/10.1016/j.imavis.2020.103944
https://doi.org/10.1016/j.imavis.2020.103944