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Application and investigation of unsupervised learning methods in retrieval and classification tasks

This site aims to share the contributions of the FAPESP research project - Young Investigators Grants - Phase 2 (grant #2018/15597-6), their related research, published papers, and shared source codes. This is an initiative for data management, scientific dissemination, and accessibility of our most recent findings, in collaboration with recognized universities.

Research Share

We develop research in the area of Computer Science thanks to essential collaborations with important universities in São Paulo (Brazil), such as São Paulo State University - Unesp and the University of Campinas - Unicamp, Federal University of São Carlos - UfsCar, and Norwegian University of Science and Technology - NTNU.

Furthermore, our work is only possible thanks to partnerships with outstanding scientific funding agencies, such as São Paulo Research Foundation - FAPESP.

Latest Publications

Graph Convolutional Networks based on manifold learning for semi-supervised image classification

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 labeled data, which is often not available, due to costs and difficulties of manual labeling processes. In this scenario, unsupervised and semi-supervised approaches have been gaining increasing attention.