Image Retrieval with Long-Term Memory Learning and Short-Time Relevance Feedback

Zhen Sun, Zhe-ming Lu, Hai Jin
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引用次数: 1

Abstract

This paper presents a framework for effective image retrieval by employing long-term memory learning together with short time relevance feedback. Considering the fuzzy characteristic of the human's semantic knowledge, the proposed retrieval framework is associated with a novel matrix named fuzzy semantic relevance matrix (FSRM), which is used for remembering the semantic information obtained from user-provided interactions. Experimental results demonstrate the effectiveness of the proposed scheme.
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基于长时记忆学习和短时相关反馈的图像检索
本文提出了一种利用长时记忆学习与短时相关反馈相结合的有效图像检索框架。考虑到人类语义知识的模糊性,本文提出的检索框架与模糊语义关联矩阵(FSRM)相关联,该矩阵用于记忆从用户提供的交互中获得的语义信息。实验结果证明了该方案的有效性。
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