Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Shafaei, Mahsa"'
We address the challenge of detecting questionable content in online media, specifically the subcategory of comic mischief. This type of content combines elements such as violence, adult content, or sarcasm with humor, making it difficult to detect.
Externí odkaz:
http://arxiv.org/abs/2406.07841
In this work, we introduce a pioneering research challenge: evaluating positive and potentially harmful messages within music products. We initiate by setting a multi-faceted, multi-task benchmark for music content assessment. Subsequently, we introd
Externí odkaz:
http://arxiv.org/abs/2309.10182
In this paper, we introduce the task of predicting severity of age-restricted aspects of movie content based solely on the dialogue script. We first investigate categorizing the ordinal severity of movies on 5 aspects: Sex, Violence, Profanity, Subst
Externí odkaz:
http://arxiv.org/abs/2109.09276
In this work, we explore different approaches to combine modalities for the problem of automated age-suitability rating of movie trailers. First, we introduce a new dataset containing videos of movie trailers in English downloaded from IMDB and YouTu
Externí odkaz:
http://arxiv.org/abs/2101.11704
Autor:
Solorio, Thamar, Shafaei, Mahsa, Smailis, Christos, Bushman, Brad J., Gentile, Douglas A., Scharrer, Erica, Stockdale, Laura, Kakadiaris, Ioannis
This White Paper summarizes the authors' discussion regarding objectionable content for the University of Houston (UH) Research Team to outline a strategy for building an extensive repository of online videos to support research into automated multim
Externí odkaz:
http://arxiv.org/abs/2104.03903
Autor:
Solorio, Thamar, Shafaei, Mahsa, Smailis, Christos, Diab, Mona, Giannakopoulos, Theodore, Ji, Heng, Liu, Yang, Mihalcea, Rada, Muresan, Smaranda, Kakadiaris, Ioannis
This white paper presents a summary of the discussions regarding critical considerations to develop an extensive repository of online videos annotated with labels indicating questionable content. The main discussion points include: 1) the type of app
Externí odkaz:
http://arxiv.org/abs/2101.10894
Autor:
Khashabi, Daniel, Cohan, Arman, Shakeri, Siamak, Hosseini, Pedram, Pezeshkpour, Pouya, Alikhani, Malihe, Aminnaseri, Moin, Bitaab, Marzieh, Brahman, Faeze, Ghazarian, Sarik, Gheini, Mozhdeh, Kabiri, Arman, Mahabadi, Rabeeh Karimi, Memarrast, Omid, Mosallanezhad, Ahmadreza, Noury, Erfan, Raji, Shahab, Rasooli, Mohammad Sadegh, Sadeghi, Sepideh, Azer, Erfan Sadeqi, Samghabadi, Niloofar Safi, Shafaei, Mahsa, Sheybani, Saber, Tazarv, Ali, Yaghoobzadeh, Yadollah
Despite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich languages like English. This work focuses on Persian language, one of t
Externí odkaz:
http://arxiv.org/abs/2012.06154
In recent years, abusive behavior has become a serious issue in online social networks. In this paper, we present a new corpus from a semi-anonymous social media platform, which contains the instances of offensive and neutral classes. We introduce a
Externí odkaz:
http://arxiv.org/abs/1909.03100
The film culture has grown tremendously in recent years. The large number of streaming services put films as one of the most convenient forms of entertainment in today's world. Films can help us learn and inspire societal change. But they can also ne
Externí odkaz:
http://arxiv.org/abs/1908.07819
Publikováno v:
In Expert Systems With Applications 15 December 2022 209
