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Unsupervised manifold learning by correlation graph and strongly connected components for image retrieval
(2014-01-28)
This paper presents a novel manifold learning approach that takes into account the intrinsic dataset geometry. The dataset structure is modeled in terms of a Correlation Graph and analyzed using Strongly Connected Components ...
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 ...
PIXELWISE TIME SERIES RETRIEVAL IN PHENOLOGICAL STUDIES
(Ieee, 2019-01-01)
The support of time series similarity searches might be crucial in phenology studies, in which long-term time series analysis based on the identification of similar and different phenological patterns shared by individuals ...
Pixelwise Time Series Retrieval in Phenological Studies
(2019-07-01)
The support of time series similarity searches might be crucial in phenology studies, in which long-term time series analysis based on the identification of similar and different phenological patterns shared by individuals ...
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 ...
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 ...
Semi-supervised learning for relevance feedback on image retrieval tasks
(Ieee, 2014-01-01)
Relevance feedback approaches have been established as an important tool for interactive search, enabling users to express their needs. However, in view of the growth of multimedia collections available, the user efforts ...
Representation Learning for Image Retrieval through 3D CNN and Manifold Ranking
(2021-01-01)
Despite of the substantial success of Convolutional Neural Networks (CNNs) on many recognition and representation tasks, such models are very reliant on huge amount of data to allow effective training. In order to improve ...
A denoising convolutional neural network for self-supervised rank effectiveness estimation on image retrieval
(2021-08-24)
Image and multimedia retrieval has established as a prominent task in an increasingly digital and visual world. Mainly supported by decades of development on hand-crafted features and the success of deep learning techniques, ...