{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T19:43:16Z","timestamp":1765827796618,"version":"3.28.0"},"reference-count":29,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T00:00:00Z","timestamp":1556668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T00:00:00Z","timestamp":1556668800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T00:00:00Z","timestamp":1556668800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,5]]},"DOI":"10.1109\/iwbf.2019.8739202","type":"proceedings-article","created":{"date-parts":[[2019,6,21]],"date-time":"2019-06-21T03:16:24Z","timestamp":1561086984000},"page":"1-6","source":"Crossref","is-referenced-by-count":21,"title":["Combating the Elsagate Phenomenon: Deep Learning Architectures for Disturbing Cartoons"],"prefix":"10.1109","author":[{"given":"Akari","family":"Ishikawa","sequence":"first","affiliation":[]},{"given":"Edson","family":"Bollis","sequence":"additional","affiliation":[]},{"given":"Sandra","family":"Avila","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","first-page":"1152","article-title":"A bag-of-features approach based on hue-SIFT descriptor for nude detection","author":"lopes","year":"2009","journal-title":"EUSIPCO"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/SIBGRAPI.2009.32"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.12.017"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.03.099"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2018.03.001"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2017.12.005"},{"key":"ref16","article-title":"RECOD at MediaEval 2014: Violent scenes detection task","author":"avila","year":"2014","journal-title":"MediaEval 2014 Workshop"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2017.50"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3230833.3232809"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00215"},{"journal-title":"On youtube kids startling videos slip past filters","year":"2017","key":"ref4"},{"key":"ref27","article-title":"Rigid-motion scattering for image classification","author":"sifre","year":"2014","journal-title":"Ph D Dissertation"},{"journal-title":"The disturbing videos that are tricking children","year":"2017","key":"ref3"},{"key":"ref6","first-page":"294","article-title":"A safer youtube kids: An extra layer of content filtering using automated multimodal analysis","author":"alghowinem","year":"2018","journal-title":"Intell"},{"key":"ref29","first-page":"4278","article-title":"Inception-v4, inception-resnet and the impact of residual connections on learning","author":"szegedy","year":"2017","journal-title":"AAAI Conference"},{"journal-title":"Crude parodies of kids movies can&#x2019;t be stopped","year":"0","author":"dailys","key":"ref5"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/INMIC.2018.8595563"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/INTECH.2016.7845111"},{"journal-title":"Youtube&#x2019;s elsagate illuminates the unintended horrors of the digital age","year":"2017","key":"ref2"},{"key":"ref9","article-title":"Disturbed youtube for kids: Characterizing and detecting disturbing content on youtube","volume":"1901 7046","author":"papadamou","year":"2019"},{"journal-title":"r\/Elsagate What is Elsagate?","year":"0","key":"ref1"},{"key":"ref20","article-title":"Squeezenet: Alexnet-level accuracy with 50x fewer parameters and <0.5mb model size","volume":"1602 7360","author":"iandola","year":"2016"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00907"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.forsciint.2016.09.010"},{"key":"ref23","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"NeurIPS"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"lecun","year":"2015","journal-title":"Nature"},{"key":"ref25","article-title":"Information technology &#x2013; coding of audiovisual objects &#x2013; part 10: Advanced video coding","volume":"9","year":"2018","journal-title":"Standard"}],"event":{"name":"2019 7th International Workshop on Biometrics and Forensics (IWBF)","start":{"date-parts":[[2019,5,2]]},"location":"Cancun, Mexico","end":{"date-parts":[[2019,5,3]]}},"container-title":["2019 7th International Workshop on Biometrics and Forensics (IWBF)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8735658\/8739167\/08739202.pdf?arnumber=8739202","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T14:46:57Z","timestamp":1658155617000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8739202\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5]]},"references-count":29,"URL":"https:\/\/doi.org\/10.1109\/iwbf.2019.8739202","relation":{},"subject":[],"published":{"date-parts":[[2019,5]]}}}