Due to the increasing availability of image and multimedia collections, unsupervised post-processing methods, which are capable of improving the effectiveness of retrieval results without the need of user intervention, ...

Semi-supervised learning methods exploit both labeled and unlabeled data items in their training process, requiring only a small subset of labeled items. Although capable of drastically reducing the costs of labeling ...

Semi-supervised learning methods exploit both labeled and unlabeled data items in their training process, requiring only a small subset of labeled items. Although capable of drastically reducing the costs of labeling ...

The huge amount of multimedia content accumulated daily has demanded the development of effective retrieval approaches. In this context, speaker recognition methods capable of automatically identifying a person through ...

Various unsupervised learning methods have been proposed with significant improvements in the effectiveness of image search systems. However, despite the relevant effectiveness gains, these approaches commonly require high ...

Initial stages of Alzheimer's disease are easily confused with the normal aging process. Additionally, the methodology involved in the diagnosis by radiologists can be subjective and difficult to document. In this scenario, ...

Research on image processing has shown that combining segmentation methods may lead to a solid approach to extract semantic information from different sort of images. Within this context, the Normalized Cut (NCut) is usually ...

This paper presents a novel unsupervised learning approach that takes into account the intrinsic dataset structure, which is represented in terms of the reciprocal neighborhood references found in different ranked lists. ...

Speaker recognition is a task of remarkable relevance, with applications in diversified domains. Recently, mainly due to the facilities in audio-visual content acquisition, the capacity of analyzing growing datasets ...