Pornographic cartoon video detection through deep neural networks
Despite the efficient solutions in pornography detection literature, specific solutions for sensitive content in cartoons have not been developed yet. In this work, we evaluate how state-of-the-art solutions for natural videos (with humans) perform in cartoons. Also, we propose a new method with hig...
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| Main Authors: | , , |
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| Format: | Online |
| Language: | English |
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Universidade Estadual de Campinas
2018
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| Online Access: | https://econtents.sbu.unicamp.br/eventos/index.php/pibic/article/view/65 |
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| _version_ | 1864358324366999552 |
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| author | Ishikawa, Akari de Avila, Sandra Eliza Fontes Perez, Mauricio Lisboa |
| author_facet | Ishikawa, Akari de Avila, Sandra Eliza Fontes Perez, Mauricio Lisboa |
| author_sort | Ishikawa, Akari |
| collection | Portal de Eventos Científicos da UNICAMP |
| container_reference | Revista dos Trabalhos de Iniciação Científica da UNICAMP; n. 26 (2018): Congresso de Iniciação Científica Unicamp |
| description | Despite the efficient solutions in pornography detection literature, specific solutions for sensitive content in cartoons have not been developed yet. In this work, we evaluate how state-of-the-art solutions for natural videos (with humans) perform in cartoons. Also, we propose a new method with higher accuracy, showing that treating cartoons independently can improve sensitive content filtering. |
| first_indexed | 2025-10-08T13:49:42Z |
| format | Online |
| id | ojs-article-65 |
| institution | Universidade Estadual de Campinas |
| issn | 2596-1969 |
| language | eng |
| last_indexed | 2025-10-08T13:49:42Z |
| publishDate | 2018 |
| publisher | Universidade Estadual de Campinas |
| record_format | ojs |
| spelling | ojs-article-652025-09-26T14:32:30Z Pornographic cartoon video detection through deep neural networks Ishikawa, Akari de Avila, Sandra Eliza Fontes Perez, Mauricio Lisboa Deep learning Pornography classification Cartoons. Despite the efficient solutions in pornography detection literature, specific solutions for sensitive content in cartoons have not been developed yet. In this work, we evaluate how state-of-the-art solutions for natural videos (with humans) perform in cartoons. Also, we propose a new method with higher accuracy, showing that treating cartoons independently can improve sensitive content filtering. Universidade Estadual de Campinas 2018-12-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Artigo de convidado application/pdf https://econtents.sbu.unicamp.br/eventos/index.php/pibic/article/view/65 10.20396/revpibic26201865 Revista dos Trabalhos de Iniciação Científica da UNICAMP; n. 26 (2018): Congresso de Iniciação Científica Unicamp 2596-1969 eng https://econtents.sbu.unicamp.br/eventos/index.php/pibic/article/view/65/50 Copyright (c) 2018 Akari Ishikawa, Sandra Eliza Fontes de Avila http://creativecommons.org/licenses/by/4.0 |
| spellingShingle | Ishikawa, Akari de Avila, Sandra Eliza Fontes Perez, Mauricio Lisboa Deep learning Pornography classification Cartoons. Pornographic cartoon video detection through deep neural networks |
| title | Pornographic cartoon video detection through deep neural networks |
| title_full | Pornographic cartoon video detection through deep neural networks |
| title_fullStr | Pornographic cartoon video detection through deep neural networks |
| title_full_unstemmed | Pornographic cartoon video detection through deep neural networks |
| title_short | Pornographic cartoon video detection through deep neural networks |
| title_sort | pornographic cartoon video detection through deep neural networks |
| topic | Deep learning Pornography classification Cartoons. |
| url | https://econtents.sbu.unicamp.br/eventos/index.php/pibic/article/view/65 |
| work_keys_str_mv | AT ishikawaakari pornographiccartoonvideodetectionthroughdeepneuralnetworks AT deavilasandraelizafontes pornographiccartoonvideodetectionthroughdeepneuralnetworks AT perezmauriciolisboa pornographiccartoonvideodetectionthroughdeepneuralnetworks |
