Accurately ranking images and multimedia objects are of paramount relevance in many
retrieval and learning tasks. Manifold learning methods have been investigated for ranking …

Contextual information, defined in terms of the proximity of feature vectors in a feature space,
has been successfully used in the construction of search services. These search systems …

Fourier descriptors are classical global shape descriptors with high matching speed but low
accuracy. To obtain higher accuracy, a novel framework for forming Fourier descriptors is …

This paper presents a robust and comprehensive graph-based rank aggregation approach,
used to combine results of isolated ranker models in retrieval tasks. The method follows an …

The relevance of diversified data preprocessing approaches for improving clustering tasks is
remarkable. Once the effectiveness is direct impacted by feature representation and …

Similarity measurement is an essential component in image retrieval systems. While
previous work is focused on generic distance estimation, this paper investigates the problem …

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 …

Due to the increasing availability of image and multimedia collections, unsupervised post-
processing methods, which are capable of improving the effectiveness of retrieval results …

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

The increasing amount of multimedia data collections available today evinces the pressing
need for methods capable of indexing and retrieving this content. Despite the continuous …