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Exploring Contextual Classification Approaches for Optimum-Path Forest

Grant number: 12/06472-9
Support Opportunities:Scholarships in Brazil - Doctorate
Start date: July 01, 2012
End date: June 30, 2016
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal Investigator:João Paulo Papa
Grantee:Daniel Osaku
Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
Associated research grant:09/16206-1 - New trends on optimum-path forest-based pattern recognition, AP.JP

Abstract

Pattern recognition techniques have attracted much attention in the last years, in which data samples are feature-based representations of images, signals and videos. However, the assumption of statistically independent data may not be handled in some situations. Therefore, the study of techniques that employ contextual information has grown in the scientific community, since it may increase the recognition rates. In this project, we propose to consider the contextual information for Optimum-Path Forest classifier, since it has neven been fone before. We also intend to stablish a relation between Markov Random Fields and Information Theory in this research, since the former has been extensively used for contextual-based classification, and the latter can also be employed for the same task.

News published in Agência FAPESP Newsletter about the scholarship:
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Scientific publications (4)
(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)
PEREIRA, DANILLO R.; PAZOTI, MARIO A.; PEREIRA, LUIS A. M.; RODRIGUES, DOUGLAS; RAMOS, CAIO O.; SOUZA, ANDRE N.; PAPA, JOAO P.. Social-Spider Optimization-based Support Vector Machines applied for energy theft detection. COMPUTERS & ELECTRICAL ENGINEERING, v. 49, p. 25-38, . (14/16250-9, 12/06472-9, 13/20387-7)
OSAKU, D.; NAKAMURA, R. Y. M.; PEREIRA, L. A. M.; PISANI, R. J.; LEVADA, A. L. M.; CAPPABIANCO, F. A. M.; FALCO, A. X.; PAPA, JOAO P.. Improving land cover classification through contextual-based optimum-path forest. INFORMATION SCIENCES, v. 324, p. 60-87, . (14/16250-9, 09/16206-1, 12/06472-9, 13/20387-7)
OSAKU, DANIEL; PEREIRA, DANILLO R.; LEVADA, ALEXANDRE L. M.; PAPA, JOAO P.. Fine-Tuning Contextual-Based Optimum-Path Forest for Land-Cover Classification. IEEE Geoscience and Remote Sensing Letters, v. 13, n. 5, p. 735-739, . (14/16250-9, 12/06472-9, 13/20387-7)
MARTINS, G. B.; AFONSO, L. C. S.; OSAKU, D.; ALMEIDA, JURANDY; PAPA, J. P.; BAYROCORROCHANO, E; HANCOCK, E. Static Video Summarization through Optimum-Path Forest Clustering. PROGRESS IN PATTERN RECOGNITION IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2014, v. 8827, p. 8-pg., . (12/06472-9, 13/20387-7)