Relevant bibliographies by topics / Offensive image detection

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  1. Journal articles
  2. Dissertations / Theses
  3. Conference papers

Academic literature on the topic 'Offensive image detection'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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Journal articles on the topic "Offensive image detection"

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Jahangard, Simindokht. "Exploring Rotation and Scale Invariant Features in Image Pla- giarism Detection Using Manifold-Ranking Algorithm." International Journal of Engineering & Technology 7, no. 4 (2018): 2663. http://dx.doi.org/10.14419/ijet.v7i4.10575.

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Plagiarism, as a crucial offense especially in academia, not only is well-known problem in text but also is becoming widespread in image. In this work, the performance of manifold-ranking, known as robust method among semi-supervised methods, has been investigated by using twelve different features. As its high performance is attributed to the quality of constructed graph, we applied robust k-regular nearest neighbor (k-RNN) graph in the framework of manifold-ranking based retrieval. Among all tested feature point detectors and descriptors, Root-SIFT, the feature point ones, due to it is invar
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Mahmoud, Tarek M., Tarek Abd-El-Hafeez, and Ahmed Omar. "A Highly Efficient Content Based Approach to Filter Pornography Websites." International Journal of Computer Vision and Image Processing 2, no. 1 (2012): 75–90. http://dx.doi.org/10.4018/ijcvip.2012010105.

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With the ever-growing Web, the Websites with objectionable contents like pornography, violence, racism, etc. have been augmented rapidly during recent years. Among the offensive contents, the pornography is the most harmful one affecting children safety and causing many destructive side effects. A content filter is one or more pieces of software that work together to prevent users from viewing material found on the Internet. This paper presents an efficient content based software system for detecting and filtering pornography images in Web pages. The proposed system runs online in the backgrou
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Newman, Jacob, Jian-Wei Lin, Dah-Jye Lee, and Jen-Jui Liu. "Automatic Annotation of American Football Video Footage for Game Strategy Analysis." Electronic Imaging 2021, no. 6 (2021): 303–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.6.iriacv-303.

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Annotation and analysis of sports videos is a challenging task that, once accomplished, could provide various benefits to coaches, players, and spectators. In particular, American Football could benefit from such a system to provide assistance in statistics and game strategy analysis. Manual analysis of recorded American football game videos is a tedious and inefficient process. In this paper, as a first step to further our research for this unique application, we focus on locating and labeling individual football players from a single overhead image of a football play immediately before the p
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Gill, Jasravia, Kamil Faisal, Ahmed Shaker, and Wai Yeung Yan. "Detection of waste dumping locations in landfill using multi-temporal Landsat thermal images." Waste Management & Research: The Journal for a Sustainable Circular Economy 37, no. 4 (2019): 386–93. http://dx.doi.org/10.1177/0734242x18821808.

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The disposal of solid waste in a conventional landfill is inevitably associated with potential adverse environmental impacts, resulting in the migration of landfill gas and offensive odors on the surrounding areas. In addition to the obnoxious fumes and hazardous leachate, heat generation is continuously observed within the landfill during the aerobic and anaerobic phases. Despite the negative impacts, such “heat generation” phenomenon can turn into valuable information to aid in detecting unauthorized landfill activities and tracing unrecorded dumping regions. The spatial distribution of wast
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Jadhav, Rachana, and Prof Vikas N. Honmane. "MEMES CLASSIFICATION SYSTEM USING COMPUTER VISION AND NLP TECHNIQUES." International Journal of Engineering Applied Sciences and Technology 6, no. 2 (2021). http://dx.doi.org/10.33564/ijeast.2021.v06i02.025.

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—A meme is a culturally relevant, and brief form of media that raise a content over the internet. Now a days posting a meme is popular communication medium, due to its multimodal nature. Postings of hateful memes or fooling, cyberbullying are growing gradually. Meme takes a major part in forming people’s trust and perspective. Meme can be quickly post by anybody, and its integrity stands compromised. Hateful and aggressive matter detection have been largely traversed in a form such as text or image. And Memes complicate the task, because some meme can have a good caption and normal pictures, b
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"Detection of Hate Speech and offensive Language on Sentiment Analysis using Machine Learning Techniques." International Journal of Innovative Technology and Exploring Engineering 9, no. 5 (2020): 136–39. http://dx.doi.org/10.35940/ijitee.e1985.039520.

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Toxic online content (TOC) has become a significant problem in current day’s world due to uses of the internet by people of distinct culture, social, organization and industries background and followed Twitter, Facebook, WhatsApp,Instagram, and telegram, etc. Even now, there is lots of work going on related to single-label classification for the text analysis and to make less comparative to errors and more efficient. But in recent years, there is a shift towards the multi-label classification, which can be applicable for both text and images. But text classification is not much popular among t
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"A Robust Algorithm for Real Time Tracking With Optical Flow." International Journal of Innovative Technology and Exploring Engineering 9, no. 1 (2019): 887–92. http://dx.doi.org/10.35940/ijitee.a4419.119119.

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Object tracking is a troublesome undertaking and significant extent in data processor perception and image handling community. Some of the applications are protection surveillance, traffic monitoring on roads, offense detection and medical imaging. In this paper a recent technique for tracking of moving object is intended. Optical flow information authorizes us to know the displacement and speed of objects personate in a scene. Apply optical flow to the image gives flow vectors of the points to distinguishing the moving aspects. Optical flow is accomplished by Lucas canade algorithm. This algo
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Urbas, Gregor, and Kendra Fouracre. "Obligations and Liability of ISPs as Guardians of Internet Content: Comparative Perspectives." Computer Law Review International 11, no. 2 (2010). http://dx.doi.org/10.9785/ovs-cri-2010-33.

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AbstractTo what extent can Internet Service Providers (ISPs) and Internet ContentHosts (ICHs) be liable for criminal and civil breaches of the law arising from the distribution of illegal Internet content such as child pornography or other offensive images? Do they have obligations to assist in the prevention and detection of crimes involving illegal content? What about material that breaches privacy, consumer protection, copyright or contract laws? If such liabilities do exist, what can ISPs do to protect themselves? These questions have been approached in several different ways around the wo
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Gagliardi, Katy. "Facebook Captions: Kindness, or Inspiration Porn?" M/C Journal 20, no. 3 (2017). http://dx.doi.org/10.5204/mcj.1258.

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IntroductionIn 2017, both the disability community and popular culture are using the term “inspiration porn” to describe one form of discrimination against people with disability. ABC’s Speechless, “a sitcom about a family with a son who has a disability, (has) tackled why it’s often offensive to call people with disabilities ‘inspirational’” (Wanshel). The reasons why inspiration porn is considered to be discriminatory have been widely articulated online by people with disability. Amongst them is Carly Findlay, a disabled writer, speaker, and appearance activist, who has written that:(inspira
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Esau, Katharina. "Hate speech (Hate Speech/Incivility)." DOCA - Database of Variables for Content Analysis, March 26, 2021. http://dx.doi.org/10.34778/5a.

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The variable hate speech is an indicator used to describe communication that expresses and/or promotes hatred towards others (Erjavec & Kova?i?, 2012; Rosenfeld, 2012; Ziegele, Koehler, & Weber, 2018). A second element is that hate speech is directed against others on the basis of their ethnic or national origin, religion, gender, disability, sexual orientation or political conviction (Erjavec & Kova?i?, 2012; Rosenfeld, 2012; Waseem & Hovy, 2016) and typically uses terms to denigrate, degrade and threaten others (Döring & Mohseni, 2020; Gagliardone, Gal, Alves, & Martí
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Dissertations / Theses on the topic "Offensive image detection"

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Belém, Ruan Josemberg Silva. "Detecção automática de conteúdo ofensivo na web." Universidade Federal do Amazonas, 2006. http://tede.ufam.edu.br/handle/tede/2932.

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Made available in DSpace on 2015-04-11T14:03:02Z (GMT). No. of bitstreams: 1 Ruan Josemberg Silva Belem.pdf: 270710 bytes, checksum: 6becb4184530c335870aefc5042c2116 (MD5) Previous issue date: 2006-05-12<br>Fundação de Amparo à Pesquisa do Estado do Amazonas<br>The World Wide Web is a huge source of diverse information, including offensive material such as pornography related content. This poses the problem of automatcally detecting offensive content as a way to avoid unauthorised access, for instance, by children or by employees during working hours. Although this sort of information is p
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Conference papers on the topic "Offensive image detection"

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Tsai, Tsung-Yu, Yen-Yu Lin, Hong-Yuan Mark Liao, and Shyh-Kang Jeng. "Recognizing offensive tactics in broadcast basketball videos via key player detection." In 2017 IEEE International Conference on Image Processing (ICIP). IEEE, 2017. http://dx.doi.org/10.1109/icip.2017.8296407.

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Barakat, M. S., C. H. Ritz, and D. A. Stirling. "Detecting offensive user video blogs: An adaptive keyword spotting approach." In 2012 International Conference on Audio, Language and Image Processing (ICALIP). IEEE, 2012. http://dx.doi.org/10.1109/icalip.2012.6376654.

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Gandhi, Shreyansh, Samrat Kokkula, Abon Chaudhuri, et al. "Scalable Detection of Offensive and Non-compliant Content / Logo in Product Images." In 2020 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE, 2020. http://dx.doi.org/10.1109/wacv45572.2020.9093454.

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