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Support for computational environments and experiments execution: weakly-supervised and classification fusion methods

Grant number: 20/11366-0
Support type:Scholarships in Brazil - Technical Training Program - Technical Training
Effective date (Start): November 01, 2020
Effective date (End): June 30, 2021
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Cooperation agreement: Microsoft Research
Principal researcher:Daniel Carlos Guimarães Pedronette
Grantee:Lucas Pascotti Valem
Home Institution: Instituto de Geociências e Ciências Exatas (IGCE). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil
Company:Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Instituto de Geociências e Ciências Exatas (IGCE)
Associated research grant:17/25908-6 - Weakly supervised learning for compressed video analysis on retrieval and classification tasks for visual alert, AP.PITE
News published in Agência FAPESP Newsletter about the scholarship:
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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
GUIMARAES PEDRONETTE, DANIEL CARLOS; PASCOTTI VALEM, LUCAS; LATECKI, LONGIN JAN. Efficient Rank-Based Diffusion Process with Assured Convergence. JOURNAL OF IMAGING, v. 7, n. 3 MAR 2021. Web of Science Citations: 0.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.