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Combining re-ranking and rank aggregation methods for image retrieval
(2016-08-01)
This paper presents novel approaches for combining re-ranking and rank aggregation methods aiming at improving the effectiveness of Content-Based Image Retrieval (CBIR) systems. Given a query image as input, CBIR systems ...
Combining Re-ranking And Rank Aggregation Methods For Image Retrieval
(SpringerDordrecht, 2016)
Unsupervised manifold learning using Reciprocal kNN Graphs in image re-ranking and rank aggregation tasks
(Elsevier B.V., 2014-02-01)
In this paper, we present an unsupervised distance learning approach for improving the effectiveness of image retrieval tasks. We propose a Reciprocal kNN Graph algorithm that considers the relationships among ranked lists ...
Contextual Spaces Re-Ranking: accelerating the Re-sort Ranked Lists step on heterogeneous systems
(2017-11-25)
Re-ranking algorithms have been proposed to improve the effectiveness of content-based image retrieval systems by exploiting contextual information encoded in distance measures and ranked lists. In this paper, we show how ...
Image re-ranking and rank aggregation based on similarity of ranked lists
(Elsevier Sci LtdOxfordInglaterra, 2013)
Image Re-Ranking Acceleration on GPUs
(Ieee, 2013-01-01)
Huge image collections are becoming available lately. In this scenario, the use of Content-Based Image Retrieval (CBIR) systems has emerged as a promising approach to support image searches. The objective of CBIR systems ...
Unsupervised manifold learning using Reciprocal kNN Graphs in image re-ranking and rank aggregation tasks
(Elsevier Science BvAmsterdamHolanda, 2014)
A scalable re-ranking method for content-based image retrieval
(Elsevier B.V., 2014-05-01)
Content-based Image Retrieval (CBIR) systems consider only a pairwise analysis, i.e., they measure the similarity between pairs of images, ignoring the rich information encoded in the relations among several images. However, ...