Projects

It aims to address the problem of pattern recognition for the creation of thematic maps via supervised learning in large sets of images from small annotated data sets.

This project address the challenges for the effective use of supervised learning in dense pixel labeling in real-world applications by increasing the robustness of the models.

It proposes the development of new approaches to deal with the processing of large sets of images but which have restrictions regarding the number of labeled samples.