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

Due to a huge volume of information in many domains, the need for classification methods is
imperious. In spite of many advances, most of the approaches require a large amount of …

Impressive advances in acquisition and sharing technologies have made the growth of
multimedia collections and their applications almost unlimited. However, the opposite is true …

Several approaches based on regression have been developed in the past few years with
the goal of improving prediction results, including the use of ranking strategies. Re-ranking …

Significant challenges still remain despite the impressive recent advances in machine
learning techniques, particularly in multimedia data understanding. One of the main …

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

In existing image retrieval algorithms, negative samples often appear at the forefront of
retrieval results. To this end, in this paper, we propose a feature fusion-based re-ranking …

In recent years, the volume of multimedia data has been rapidly increasing across various
applications. Consequently, classification methods capable of handling scenarios with …

The revolutionary advances in image representation have led to impressive progress in
many image understanding-related tasks, primarily supported by Convolutional Neural …

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