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Learning-based Approach for Semantic Image Retrieval by using a dynamic Semantic Network

机译:使用动态语义网络的语义图像检索基于学习方法

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摘要

Nowadays, Image retrieval systems, emphasize the combining of high level semantics and low level visual features in the image indexing process and of course the performance of such systems for image retrieval is increased with perfect semantic network. In this research, a dynamic high level semantic network in synonym sets of keywords is used and a dynamic approach is presented for updating the semantic network and semantic contents of the images in an interactive way. The proposed approach, certainly, executes a novel kind of long term learning-based on user's opinion in the several interactions with system, and relates the behavior of system to the behavior of users in the recognition process of semantic similarity between the images. The evaluating results of system's performance show improving the accuracy of semantic network and semantic contents related to the images after applying the long term learning process.
机译:如今,图像检索系统,强调了图像索引过程中的高级语义和低级视觉特征的组合,当然,通过完美的语义网络增加了这种图像检索系统的性能。在该研究中,使用同义词中的动态高电平语义网络,并且呈现动态方法以以交互方式更新图像的语义网络和图像的语义内容。当然,拟议的方法肯定地执行基于用户在与系统的多个交互中的用户意见的新颖的长期学习,并且将系统的行为与用户之间的语义相似度的识别过程中的识别过程中的行为相关联。在应用长期学习过程之后,系统性能的评估结果提高了语义网络和与图像相关的语义内容的准确性。

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