Explicit content detection system: An approach towards a safe and ethical environment

22Citations
Citations of this article
41Readers
Mendeley users who have this article in their library.

This article is free to access.

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.

Cite

CITATION STYLE

APA

Qamar Bhatti, A., Umer, M., Adil, S. H., Ebrahim, M., Nawaz, D., & Ahmed, F. (2018). Explicit content detection system: An approach towards a safe and ethical environment. Applied Computational Intelligence and Soft Computing, 2018. https://doi.org/10.1155/2018/1463546

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free