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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Unsupervised rank diffusion for content-based image retrieval

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Author(s):
Guimaraes Pedronette, Daniel Carlos ; Torres, Ricardo da S.
Total Authors: 2
Document type: Journal article
Source: Neurocomputing; v. 260, p. 478-489, OCT 18 2017.
Web of Science Citations: 0
Abstract

Despite the continuous development of features and mid-level representations, effectively and reliably measuring the similarity among images remains a challenging problem in image retrieval tasks. Once traditional measures consider only pairwise analysis, context-sensitive measures capable of exploiting the intrinsic manifold structure became indispensable for improving the retrieval performance. In this scenario, diffusion processes and rank-based methods are the most representative approaches. This paper proposes a novel hybrid method, named rank diffusion, which uses a diffusion process based on ranking information. The proposed method consists in a diffusion-based re-ranking approach, which propagates contextual information through a diffusion process defined in terms of top-ranked objects, reducing the computational complexity of the proposed algorithm. Extensive experiments considering a rigorous experimental protocol were conducted on six public image datasets and several different descriptors. Experimental results and comparison with state-of-the-art methods demonstrate that high effectiveness gains can be obtained, despite the low-complexity of the algorithm proposed. (C) 2017 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 13/50155-0 - Combining new technologies to monitor phenology from leaves to ecosystems
Grantee:Leonor Patricia Cerdeira Morellato
Support type: Research Program on Global Climate Change - University-Industry Cooperative Research (PITE)
FAPESP's process: 13/08645-0 - Re-Ranking and rank aggregation approaches for image retrieval tasks
Grantee:Daniel Carlos Guimarães Pedronette
Support type: Research Grants - Young Investigators Grants
FAPESP's process: 13/50169-1 - Towards an understanding of tipping points within tropical South American biomes
Grantee:Ricardo da Silva Torres
Support type: Research Grants - Research Partnership for Technological Innovation - PITE