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Unsupervised distance learning by rank correlation measures for image retrieval
(2015-06-22)
Ranking accurately collection images is the main objective of Content-based Image Retrieval (CBIR) systems. In fact, the set of images ranked at the first positions generally defines the effectiveness of provided search ...
A rank aggregation framework for video interestingness prediction
(2017-01-01)
Often, different segments of a video may be more or less attractive for people depending on their experience in watching it. Due to this subjectiveness, the challenging task of automatically predicting whether a video ...
Unsupervised Effectiveness Estimation Through Intersection of Ranking References
(2019-01-01)
Estimating the effectiveness of retrieval systems in unsupervised scenarios consists in a task of crucial relevance. By exploiting estimations which dot not require supervision, the retrieval results of many applications ...
Comparing rankings from using TODIM and a fuzzy expert system
(2015-01-01)
TODIM is, in its original formulation, an MCDA method developed to solve ranking problems. As an MCDA method TODIM combines the use of a multi-attribute value function as well as elements of the Outranking Approach, being ...
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 ...
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 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 ...
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 ...
An unsupervised genetic algorithm framework for rank selection and fusion on image retrieval
(2019-06-05)
Despite the major advances on feature development for low and mid-level representations, a single visual feature is often insufficient to achieve effective retrieval results in different scenarios. Since diverse visual ...