Despite the advances in machine learning techniques, similarity assessment among
multimedia data remains a challenging task of broad interest in computer science …

Laplacian Eigenmaps (LE) is a widely used dimensionality reduction and data
reconstruction method. When the data has multiple connected components, the LE method …

The representation of multimedia content experienced tremendous advances in the last
decades. Mainly supported by deep learning models, impressive results have been …

Despite the impressive advances in image under-standing approaches, defining similarity
among images remains a challenging task, crucial for many applications such as …

In the last few decades, diffusion processes have been widely used to solve visual re-
ranking problems. The key point of these approaches is that, by diffusing the baseline …

In recent years, the amount of image data has increased exponentially, driven by
advancements in digital technologies. As the volume of data expands, the efforts required for …

Image retrieval approaches typically involve two fundamental stages: visual content
representation and similarity measurement. Traditional methods rely on pairwise …

Due to the great applicability of time series in diverse scenarios, such as medicine,
agriculture, economics, and science, the analysis and processing of this kind of data is …

Em geral, os sistemas de recuperação de imagens realizam comparações considerando
apenas pares de imagens e acabam por não levar em consideração as informações …

Multivariate time series find applications in various domains, and it is crucial to have tools for
effectively manipulating this type of data. Currently, state-of-the-art algorithms for multivariate …