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Exploring Abstract Concepts for Imag...

Galfre, Gabriele.

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Exploring Abstract Concepts for Images Privacy Classification in Social Media.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Exploring Abstract Concepts for Images Privacy Classification in Social Media./
作者:	Galfre, Gabriele.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	111 p.
附註:	Source: Masters Abstracts International, Volume: 81-11.
Contained By:	Masters Abstracts International81-11.
標題:	Computer science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27987588
ISBN:	9798641844909

Exploring Abstract Concepts for Images Privacy Classification in Social Media.
Galfre, Gabriele.

Exploring Abstract Concepts for Images Privacy Classification in Social Media. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 111 p.

Source: Masters Abstracts International, Volume: 81-11.

Thesis (M.S.)--University of Illinois at Chicago, 2019.

This item must not be sold to any third party vendors.

Automatically detecting the private nature of images posted in social networks such as Facebook, Flickr, and Instagram, is a long-standing goal considering the pervasiveness of these networks. Several prior works to image privacy prediction showed that object tags, either manually annotated or automatically extracted from images, are highly informative about images' privacy. However, we conjecture that other aspects of images captured by abstract concepts (e.g., religion, sikhism, spirituality) can improve the performance of models that use only the concrete objects from an image (e.g., temple and person). Several experimental setups have been defined to investigate how the usage of these type of information influence the performance of privacy classifiers. Results on a Flickr dataset show that the abstract concepts are better capturing the privacy nature of images, but with concrete object tags they complement each other, yielding the best performance when used in combination as features for image privacy prediction.

ISBN: 9798641844909Subjects--Topical Terms:

523869
Computer science.
Subjects--Index Terms:

Social networks

Exploring Abstract Concepts for Images Privacy Classification in Social Media.
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