Daisy Imbaquingo, M. Ortega-Bustamante, José Jácome, Tatyana K. Saltos-Echeverría, Roger Vaca
{"title":"基于计算机视觉技术的智能手机不恰当图像检测","authors":"Daisy Imbaquingo, M. Ortega-Bustamante, José Jácome, Tatyana K. Saltos-Echeverría, Roger Vaca","doi":"10.54941/ahfe1001443","DOIUrl":null,"url":null,"abstract":"In recent years, the use of smartphones in children and adolescents has increased by a considerable number and, therefore, the dangers faced by this population are increasing. Due to this, it is important to develop a technological solution that allows combat this problem by making use of computer vision. Through a bibliographic review, it has been detected those children and adolescents frequently view violent and pornographic images, this allowed us to build a dataset of this type of images to develop an artificial intelligence model. It was successfully developed under the training and validation phases using a google supercomputer (Google Colab), while for the testing phase it was implemented on an android mobile device, using screenshots, images were extracted that the screen projected, and thus later the results were analyzed under statistics using R studio. The computational model detected, with a large percentage of true positives, images and videos of a pornographic and violent nature captured from the screen resolution of a smartphone while the user was using it normally.","PeriodicalId":405313,"journal":{"name":"Artificial Intelligence and Social Computing","volume":"119 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Detection of inappropriate images on smartphones based on computer vision techniques\",\"authors\":\"Daisy Imbaquingo, M. Ortega-Bustamante, José Jácome, Tatyana K. Saltos-Echeverría, Roger Vaca\",\"doi\":\"10.54941/ahfe1001443\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, the use of smartphones in children and adolescents has increased by a considerable number and, therefore, the dangers faced by this population are increasing. Due to this, it is important to develop a technological solution that allows combat this problem by making use of computer vision. Through a bibliographic review, it has been detected those children and adolescents frequently view violent and pornographic images, this allowed us to build a dataset of this type of images to develop an artificial intelligence model. It was successfully developed under the training and validation phases using a google supercomputer (Google Colab), while for the testing phase it was implemented on an android mobile device, using screenshots, images were extracted that the screen projected, and thus later the results were analyzed under statistics using R studio. The computational model detected, with a large percentage of true positives, images and videos of a pornographic and violent nature captured from the screen resolution of a smartphone while the user was using it normally.\",\"PeriodicalId\":405313,\"journal\":{\"name\":\"Artificial Intelligence and Social Computing\",\"volume\":\"119 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Artificial Intelligence and Social Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54941/ahfe1001443\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence and Social Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54941/ahfe1001443","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection of inappropriate images on smartphones based on computer vision techniques
In recent years, the use of smartphones in children and adolescents has increased by a considerable number and, therefore, the dangers faced by this population are increasing. Due to this, it is important to develop a technological solution that allows combat this problem by making use of computer vision. Through a bibliographic review, it has been detected those children and adolescents frequently view violent and pornographic images, this allowed us to build a dataset of this type of images to develop an artificial intelligence model. It was successfully developed under the training and validation phases using a google supercomputer (Google Colab), while for the testing phase it was implemented on an android mobile device, using screenshots, images were extracted that the screen projected, and thus later the results were analyzed under statistics using R studio. The computational model detected, with a large percentage of true positives, images and videos of a pornographic and violent nature captured from the screen resolution of a smartphone while the user was using it normally.