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- W2182953902 abstract "It is no secret that pornographic material is now a one-click-away from everyone, including children and minors. General social media networks are striving to isolate adult images and videos from normal ones. Intelligent image analysis methods can help to automatically detect and isolate questionable images in media. Unfortunately, these methods require vast experience to design the classifier including one or more of the popular computer vision feature descriptors. We propose to build a classifier based on one of the recently flourishing deep learning techniques. Convolutional neural networks contain many layers for both automatic features extraction and classification. The benefit is an easier system to build (no need for hand-crafting features and classifiers). Additionally, our experiments show that it is even more accurate than the state of the art methods on the most recent benchmark dataset." @default.
- W2182953902 created "2016-06-24" @default.
- W2182953902 creator A5039652309 @default.
- W2182953902 date "2015-11-28" @default.
- W2182953902 modified "2023-09-27" @default.
- W2182953902 title "Applying deep learning to classify pornographic images and videos." @default.
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