Explicit Content Detection System: An Approach towards a Safe and Ethical Environment

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 f...

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Main Authors: Ali Qamar Bhatti, Muhammad Umer, Syed Hasan Adil, Mansoor Ebrahim, Daniyal Nawaz, Faizan Ahmed
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Applied Computational Intelligence and Soft Computing
Online Access:http://dx.doi.org/10.1155/2018/1463546
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author Ali Qamar Bhatti
Muhammad Umer
Syed Hasan Adil
Mansoor Ebrahim
Daniyal Nawaz
Faizan Ahmed
author_facet Ali Qamar Bhatti
Muhammad Umer
Syed Hasan Adil
Mansoor Ebrahim
Daniyal Nawaz
Faizan Ahmed
author_sort Ali Qamar Bhatti
collection DOAJ
description 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.
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institution Kabale University
issn 1687-9724
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language English
publishDate 2018-01-01
publisher Wiley
record_format Article
series Applied Computational Intelligence and Soft Computing
spelling doaj-art-9fd54ebf5a1d4104a8b8084fb0218c362025-02-03T01:07:00ZengWileyApplied Computational Intelligence and Soft Computing1687-97241687-97322018-01-01201810.1155/2018/14635461463546Explicit Content Detection System: An Approach towards a Safe and Ethical EnvironmentAli Qamar Bhatti0Muhammad Umer1Syed Hasan Adil2Mansoor Ebrahim3Daniyal Nawaz4Faizan Ahmed5Iqra University, PakistanIqra University, PakistanIqra University, PakistanSunway University, MalaysiaIqra University, PakistanIqra University, PakistanAn 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.http://dx.doi.org/10.1155/2018/1463546
spellingShingle Ali Qamar Bhatti
Muhammad Umer
Syed Hasan Adil
Mansoor Ebrahim
Daniyal Nawaz
Faizan Ahmed
Explicit Content Detection System: An Approach towards a Safe and Ethical Environment
Applied Computational Intelligence and Soft Computing
title Explicit Content Detection System: An Approach towards a Safe and Ethical Environment
title_full Explicit Content Detection System: An Approach towards a Safe and Ethical Environment
title_fullStr Explicit Content Detection System: An Approach towards a Safe and Ethical Environment
title_full_unstemmed Explicit Content Detection System: An Approach towards a Safe and Ethical Environment
title_short Explicit Content Detection System: An Approach towards a Safe and Ethical Environment
title_sort explicit content detection system an approach towards a safe and ethical environment
url http://dx.doi.org/10.1155/2018/1463546
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