基于半监督学习的双线性映射图像检索
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中北大学,中北大学

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TP391

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国家自然科学基金(61379080),国家科技支撑计划基金(2013BAH45F02)


A Image Retrieval Methode Of Double Biliner Mapping Based On Semi-Supervised Learning
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    摘要:

    “语义鸿沟”是基于内容图像检索中广泛存在的问题。近年来,人们为减小语义鸿沟开展了许多研究工作,并将半监督学习方法用于其中。目前,多数的检索方法只考虑数据点的结构信息,或关注点集中在低层特征。为了充分利用结构信息缩小低层特征和高层语义之间的语义鸿沟,提出了一种半监督的双映射机器学习图像检索法。该方法在低层特征与标签之间建立双线性映射,最后使用Corel图像库同流行嵌入法进行对比,实验表明所提出的方法在检索过程中可以获得较好的效果,精准率有明显提高。

    Abstract:

    "Semantic gap" is a widespread problem of content-based image retrieval. In order to reduce the semantic gap a lot of research work has been carried out in recent years, and will semi-supervised learning is applied to the field of image retrival. Current research on content-based image either just consider the data points’ structure information or not fully take into consideration of the semantic gap between low -level features and high-level semantics. To make full use of the structure information and fill the semantic gap between low-level features and high- level semantics, a new image retrieval method is introduced, which is based on semi-supervised machine learning and bilinear mapping. This method is established double bilinear mapping between low-level features and labels .We compare it against the Flexible Manifold Embedding and show a significant improvement in terms of accuracy and stability based on a subset of the Corel image gallery.

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高金金,尹四清. 基于半监督学习的双线性映射图像检索[J]. 科学技术与工程, 2014, 14(4): .
GAO Jin-jin, YIN Si-qing. A Image Retrieval Methode Of Double Biliner Mapping Based On Semi-Supervised Learning[J]. Science Technology and Engineering,2014,14(4).

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历史
  • 收稿日期:2013-08-25
  • 最后修改日期:2013-10-08
  • 录用日期:2013-10-23
  • 在线发布日期: 2014-02-28
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