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Massive-scale image retrieval based on deep visual feature representation
Journal of Visual Communication and Image Representation ( IF 2.6 ) Pub Date : 2019-12-06 , DOI: 10.1016/j.jvcir.2019.102738
Hongpeng Zhu

This paper proposes an image retrieval algorithm towards massive-scale multimedia data. In order to be consistent with human visual system, we first design a color attention function to describe the important of different image patches. Subsequently, we combine color and texture to construct candidate regions, which will be fed into a deep neural network (DNN) for deep representation extraction. Then, we design a similarity function to calculate the distance among different images, where top-ranking images are considered as the required images. Experimental results show the effectiveness and robustness of our proposed method.



中文翻译:

基于深度视觉特征表示的大规模图像检索

提出了一种针对大规模多媒体数据的图像检索算法。为了与人类视觉系统保持一致,我们首先设计一种颜色注意功能来描述不同图像斑块的重要性。随后,我们将颜色和纹理组合起来以构造候选区域,将其输入到深度神经网络(DNN)中以进行深度表示提取。然后,我们设计一个相似度函数来计算不同图像之间的距离,其中排名最高的图像被视为必需的图像。实验结果表明了该方法的有效性和鲁棒性。

更新日期:2019-12-06
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