CV Lattes
Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Graduated in Computer Science at ICMC-USP, focusing on Artificial Intelligence, Computer Vision and Machine Learning. Pursuing a Master's Degree at the Instituto de Matemática e Estatística of the University of São Paulo. Worked as a research intern in the Centre for Vision, Speech and Signal Processing of the University of Surrey - United Kingdom. Worked as a research intern in IBM's Brazil Research Lab, in the Visual Analytics team. (Source: Lattes Curriculum)
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Segmentation and recognition in medical imaging of fetuses and children, as well as non-standard individuals (e.g. patients with missing organs after major surgery), presents important challenges. One of the main reasons is that most of the state-of-art methods have been developed and applied to standard models and data (typically adults). Similar challenges arise on the continuous study …
The incremental learning approach needs the dynamic addition of information extracted from observations. This kind of learning is important in applications in which the observations are not available for the creation of the classifier since the beginning of the process. Thus, multiple training procedures are necessary to complete the learning. The optimum-path forest classifier (OPF) is c…
Anomaly detection is the problem of finding patterns with an unexpected behavior. Classification-based techniques are usually a good choice in this scenario, but require sufficient labeled data from both normal and abnormal classes. In this project we focus on a method which models relationship among examples in the feature space, by using a optimum path forest (OPF). This method interpre…
| 2 / 2 | Completed scholarships in Brazil |
| 1 / 1 | Completed scholarships abroad |
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