CV Lattes
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Universidade Estadual de Campinas (UNICAMP). Instituto de Computação (IC) (Institutional affiliation from the last research proposal) Birthplace: Peru
Data Scientist and Machine Learning Engineer, with a master's and Ph.D. in Computer Science from UNICAMP. During his Ph.D., conducted in partnership with the University of Lorraine, France, his research focused on semantic segmentation, developing new learning techniques to improve spatial accuracy in deep learning models. Additionally, he is currently pursuing an MBA in Software Engineering at the University of São Paulo (USP).During his Ph.D., he worked on semantic segmentation, developing new techniques to enhance the accuracy of deep learning models, using Gaussian mixture to cluster features and optimize results.Currently, he works at SiDi Samsung, in Campinas, focusing on the modeling, training, and interpretation of NLP models for the development of the Bixby app, designed for cell phones, TVs, watches, stoves, and refrigerators.Areas of interest include Machine Learning, Deep Learning, Natural Language Processing, Pattern Recognition, and Computer Vision. (Source: Lattes Curriculum)
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Semantic segmentation task aims to create a dense classification by labeling pixel-wise each object present in images or videos. Convolutional neural network (CNN) approaches have been proved useful by exhibiting the best results in this task. Some challenges remain, however, such as the low-resolution of feature maps and the loss of spatial precision, both produced in the last convolutio…
Semantic segmentation task aims to create a dense classification by labeling pixel-wise each object present in images or videos. Convolutional neural network (CNN) approaches have been proved useful by exhibiting the best results in this task. Some challenges remain, however, such as the low-resolution of feature maps and the loss of spatial precision, both produced in the CNNs by limited…
| 1 / 1 | Completed scholarships in Brazil |
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