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Efficient Rank-Based Diffusion Process with Assured Convergence
2021
Journal of Imaging
Visual features and representation learning strategies experienced huge advances in the previous decade, mainly supported by deep learning approaches. However, retrieval tasks are still performed mainly based on traditional pairwise dissimilarity measures, while the learned representations lie on high dimensional manifolds. With the aim of going beyond pairwise analysis, post-processing methods have been proposed to replace pairwise measures by globally defined measures, capable of analyzing
doi:10.3390/jimaging7030049
pmid:34460705
fatcat:wulsw3xk5veizecta5ugge27ha