Explicit Content Detection System: An Approach towards a Safe and Ethical Environment. (4th July 2018)

• Record Type: Journal Article
• Authors: Qamar Bhatti, Ali; Umer, Muhammad; Adil, Syed Hasan; Ebrahim, Mansoor; Nawaz, Daniyal; Ahmed, Faizan
• Other Names: Yang Miin-Shen Academic Editor.
• Is Part Of: Applied computational intelligence and soft computing. Volume 2018(2018)
• Publication Date: 2018-07-04
• Subjects: Computational intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• DOI: 10.1155/2018/1463546
• Languages: English
• ISSNs: 1687-9724

Abstract

Abstract : An explicit content detection (ECD) system to detect Not Suitable For Work (NSFW) media (i.e., image/ video) content is proposed. The proposed ECD system is based on residual network (i.e., deep learning model) which returns a probability to indicate the explicitness in media content. The value is further compared with a defined threshold to decide whether the content is explicit or nonexplicit. The proposed system not only differentiates between explicit/nonexplicit contents but also indicates the degree of explicitness in any media content, i.e., high, medium, or low. In addition, the system also identifies the media files with tampered extension and label them as suspicious. The experimental result shows that the proposed model provides an accuracy of ~ 95% when tested on our image and video datasets.