{"title":"基于深度学习的媒体篡改检测技术在高等教育教学资源保护中的应用研究","authors":"Tao Luan, Maria Amelia E. Damian","doi":"10.47852/bonviewcetr232011480604","DOIUrl":null,"url":null,"abstract":"With the rapid development of digital technology, the problem of media tampering has become increasingly serious, and higher education teaching resources are facing a crisis from image tampering and sound tampering to video tampering and even deep forgery, which brings great challenges to education work. Through deep learning, tampering can be automatically detected and self-learning and optimized in the process of detection, so that it can remain efficient and accurate in the face of new tampering techniques. The purpose of this paper is to discuss in detail the application of deep learning in media tampering detection and to explore its application in the protection of higher education teaching resources.","PeriodicalId":221229,"journal":{"name":"Contemporary Education and Teaching Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Study on the Application of Deep Learning-based Media Tampering Detection Technology in Higher Education Teaching Resource Protection\",\"authors\":\"Tao Luan, Maria Amelia E. Damian\",\"doi\":\"10.47852/bonviewcetr232011480604\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid development of digital technology, the problem of media tampering has become increasingly serious, and higher education teaching resources are facing a crisis from image tampering and sound tampering to video tampering and even deep forgery, which brings great challenges to education work. Through deep learning, tampering can be automatically detected and self-learning and optimized in the process of detection, so that it can remain efficient and accurate in the face of new tampering techniques. The purpose of this paper is to discuss in detail the application of deep learning in media tampering detection and to explore its application in the protection of higher education teaching resources.\",\"PeriodicalId\":221229,\"journal\":{\"name\":\"Contemporary Education and Teaching Research\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Contemporary Education and Teaching Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47852/bonviewcetr232011480604\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Contemporary Education and Teaching Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47852/bonviewcetr232011480604","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Study on the Application of Deep Learning-based Media Tampering Detection Technology in Higher Education Teaching Resource Protection
With the rapid development of digital technology, the problem of media tampering has become increasingly serious, and higher education teaching resources are facing a crisis from image tampering and sound tampering to video tampering and even deep forgery, which brings great challenges to education work. Through deep learning, tampering can be automatically detected and self-learning and optimized in the process of detection, so that it can remain efficient and accurate in the face of new tampering techniques. The purpose of this paper is to discuss in detail the application of deep learning in media tampering detection and to explore its application in the protection of higher education teaching resources.