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Graph-based selective rank fusion for unsupervised image retrieval
(2020-07-01)
Nowadays, there is a great variety of visual features available for image retrieval tasks. While fusion strategies have been established as a promising alternative, an inherent difficulty in unsupervised scenarios is the ...
Rank diffusion for context-based image retrieval
(2016-06-06)
This paper presents an efficient diffusion-based re-ranking approach. The proposed method propagates contextual information defined in terms of top-ranked objects of ranked lists in a diffusion process. That makes the ...
Unsupervised Effectiveness Estimation for Image Retrieval Using Reciprocal Rank Information
(2015-10-30)
In this paper, we present an unsupervised approach for estimating the effectiveness of image retrieval results obtained for a given query. The proposed approach does not require any training procedure and the computational ...
A multi-level rank correlation measure for image retrieval
(2021-01-01)
Accurately ranking the most relevant elements in a given scenario often represents a central challenge in many applications, composing the core of retrieval systems. Once ranking structures encode relevant similarity ...
A Multi-level Rank Correlation Measure for Image Retrieval
(Scitepress, 2021-01-01)
Accurately ranking the most relevant elements in a given scenario often represents a central challenge in many applications, composing the core of retrieval systems. Once ranking structures encode relevant similarity ...
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 ...
A New Family of Distance Functions for Perceptual Similarity Retrieval of Medical Images
(SPRINGER, 2009)
A long-standing challenge of content-based image retrieval (CBIR) systems is the definition of a suitable distance function to measure the similarity between images in an application context which complies with the human ...
Unsupervised measures for estimating the effectiveness of image retrieval systems
(2013-12-01)
The main objective of Content-Based Image Retrieval (CBIR) systems is to retrieve a ranked list containing the most similar images of a collection given a query image, by taking into account their visual content. Although ...
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, ...
Coordinated multiple views to support image retrieval
(University of Paris DescartesInformation Visualisation Society - IVSParis, 2014-07)
The number of images available has grown over the years, as well as the number of techniques to aid to organizing and retrieving from image collections. Techniques and systems have been proposed to recover images based on ...