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

Image classification is a critical topic due to its wide application and several challenges
associated. Despite the huge progress made last decades, there is still a demand for context …

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 …

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 …

Over the last decade, significant advances have been achieved by machine learning
approaches, notably in supervised learning scenarios. Supported by the advent of deep …

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

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 …

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