CV Lattes
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Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Instituto de Geociências e Ciências Exatas (IGCE) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Received his bachelor's degree from the Methodist University of Piracicaba, Brazil in 2001, his master's degree from the Federal University of Sao Carlos, Brazil in 2006, and his Ph.D. from the University of Sao Paulo, Brazil in 2010, with a collaborative period at the University of Alberta, Canada. He is currently an associate professor at Sao Paulo State University, Brazil. His research interests include machine learning, pattern recognition, image processing, artificial neural networks, complex networks, and nature-inspired computing. (Source: Lattes Curriculum)
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Many interactive image segmentation approaches are based on semi-supervised learning, which employs both labeled and unlabeled data in its training process. In this kind of approach, an human specialist label a few pixels from each segment, and then the semi-supervised learning algorithm labels the remaining pixels. The particle competition and cooperation model is a recent semi-supervise…
(Only some records are available in English at this moment)
Aprendizado Semi-Supervisionado é uma categoria de importância crescente no aprendizado de máquina, onde apenas um pequeno subconjunto dos dados é rotulado. Uma abordagem recente desta categoria é o modelo de competição e cooperação entre partículas, no qual itens de dados são transformados em vértices de um grafo, e arestas são criadas entre vértices representando dados semelhantes, de a…
With the great growth of quality image capture, sports broadcasts have become increasingly detailed with statistics and visual effects. The use of visual effects in plays and experts to analyze the plays contribute to the transmission of the match, generating more data and improving the experience of the spectator and coaches who use this device to correct defects in their tactics. Thus, …
This work has an objective to realize audio processing with the proposal to reduce the possible noises in the signal, because these noises can be harmful to the understanding and utilization of the audio. Systems that uses audio signals can be victims of these noises that can prejudice the operation. Thus, many of them have a preprocessing step that performs an audio denoising before the …
(Only some records are available in English at this moment)
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