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- W4312328679 abstract "To achieve multi-class image reranking, a novel image reranking algorithm using multiple discrete-time quantum walk is proposed. In this algorithm, a weighted undirected complete graph is first constructed, in which the nodes for the graph represent the images and the weighted values of these edges are the similarity value between the images. Secondly, it uses the spectral clustering to divide the images into <tex xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>$k$</tex> classes and finds the representative image of each class. Thirdly, it uses the <tex xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>$k$</tex> representative images as the initial state of quantum system, and the flip-flop shift operator and the weighted coin operator are used to control multiple discrete-time quantum walk on the weighted complete graph. Finally, the average probability values of the walker reaching the node of the graph is used as the relevance scores of the image, and then the images are reranked by the relevance scores. the experimental results show that our scheme has a significant enhance compared with the initial ranking algorithm from the comparison of visual and relevance scores. Furthermore, the effectiveness of our algorithm is evaluated by the average precision (AP) and the mean average precision (MAP), where the AP of our algorithm is increased by 53.21%, 31.75% and 14.29% for three types of the query image in randomly selected image group respectively, and the MAP of our algorithm is increased by 29.57% for all image groups compared with the initial ranking algorithm." @default.
- W4312328679 created "2023-01-04" @default.
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- W4312328679 date "2022-08-01" @default.
- W4312328679 modified "2023-09-27" @default.
- W4312328679 title "A Multi-class image reranking algorithm based on multiple discrete-time quantum walk" @default.
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- W4312328679 doi "https://doi.org/10.1109/ccpqt56151.2022.00078" @default.
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