The Semantic Label Automatic Sorting Based on the Base Classifier Weighted Voting

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Abstract:

The ranking results of semantic label are the important reference index on the point whether the image sematic automatic tagging results are right. To the problem of the disorder of the current image sematic labels, this paper suggests a method of the image semantic label automatic sorting which is based on the base classifier weighted voting. This method based on the content in the significant image regional, it weighted votes on every part of the semantic label, with the help of the base classifier. In this way, it tests the relevance of each semantic label and the image that makes the right order of the image label.

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476-479

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February 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Tianfeng, Sheng xukun, Du ruishan, Zhou kai. Image Annotation Based on Multiple Feature Tag Relevance Learning[J], Journal of System Simulation. 2013, 25(2).

Google Scholar

[2] Huang Yan, Sun Jian, Gu Yu. Summary of the Researches on Multi-Label Image Annotation[J], Journal of Yunnan University Nationalities(Natural Sciences Edition). 2011, 20(6).

Google Scholar

[3] Xu Hongtao, ZhouXiangdong, XiangYu, ShiBaile. Adaptive Model for Web Image Semantic Annotation[J]. Journal Of Software, 2010, 21(9).

Google Scholar

[4] Li J, Wang J. Automatic linguistic indexing of pictures by a statistical modeling approach, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003(19).

DOI: 10.1109/tpami.2003.1227984

Google Scholar

[5] Lou Ying, LiZhanghuai, ChenQun, ZhangLijun. Effective XML keyword search with considering semantics of tags. Journal of Huazhong University of Science And Technology Nature Science. 2011, 39(9).

Google Scholar

[6] Zhao yinghai, ZhaZhengjun, LiShanshan, WuXiuqing. Automatic image tag ranking scheme based on visual content semantic relatedness. JOURNAL OF UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA. 2011, 41(2).

Google Scholar

[7] Bai Hua. Researches on the Semantic Control to User Tagging, JOURNAL OF INTELLIGENCE. 2009, 28(11).

Google Scholar

[8] Zhuang Jinfeng, Hoi S C H. A two-view learning approach for image tag ranking[A]. Proceedings of ACM International Conference on Web Search and Data Mining[C]. Hong Kong, China: ACM, 2011: 625-634.

DOI: 10.1145/1935826.1935913

Google Scholar

[9] Li Xiong, Snoek C.G. M, Worring M. Learning tag relevance by neihbor voting for social Image retrieval[A]. Proceedings of ACM International Conference on Multi-media Information Retrieval[C]. Vancouver, Canada: ACM, 2008: 180-187.

DOI: 10.1145/1460096.1460126

Google Scholar