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Journal of Imaging, Volume 7, Issue 3
March 2021 - 20 articles
Cover Story: Visual features have experienced huge advances in the last decade. However, even in the era of deep learning, retrieval systems often perform comparisons by computing measures that consider only pairs of images and ignore the relevant information encoded in the relationships among images. To go beyond pairwise analysis, post-processing methods have been proposed. Among them, two categories can be highlighted as very representative: diffusion processes and rank-based approaches. In this paper, an efficient rank-based diffusion process is proposed, combining both approaches and avoiding the drawbacks of each. The method is capable of approximating a diffusion process based only on the top positions of ranked lists, while ensures its convergence. View this paper
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J. Imaging - ISSN 2313-433X