Advanced search
Start date
Betweenand

Study and development of new Kernel functions with applications on remote sensing image classification

Abstract

Pattern Recognition is a Computer Science area which aims to deal with classification problems. Remote Sensing image classification is one of the most important applications of Pattern Recognition in environmental studies. Face to the importance of achieve more accurate classification results, develop and enhance image classification techniques is a constant motivation. The emergence of kernel functions has revolutionized Pattern Recognition researches and consequently image classification application, further expanding the research area. This project proposes the study and development of new kernel functions for image classification, aiming to produce more accurate results compared to usual kernels. The validation of the kernels developed from this research will be done using simulated images and practical studies about land use and land cover classification in Brazilian Amazon. (AU)

Articles published in Agência FAPESP Newsletter about the research grant:
Articles published in other media outlets (0 total):
More itemsLess items
VEICULO: TITULO (DATA)
VEICULO: TITULO (DATA)

Scientific publications (7)
(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)
NEGRI, R. G.; DUTRA, L. V.; SANT'ANNA, S. J. S.; LU, D.. Examining region-based methods for land cover classification using stochastic distances. International Journal of Remote Sensing, v. 37, n. 8, p. 1902-1921, . (14/14830-8)
NEGRI, ROGERIO GALANTE; DA SILVA, ERIVALDO ANTONIO; CASACA, WALLACE. Inducing Contextual Classifications With Kernel Functions Into Support Vector Machines. IEEE Geoscience and Remote Sensing Letters, v. 15, n. 6, p. 962-966, . (13/07375-0, 17/03595-6, 14/08822-2, 14/14830-8)
NEGRI, R. G.; DUTRA, L. V.; SANT'ANNA, S. J. S.. Comparing support vector machine contextual approaches for urban area classification. REMOTE SENSING LETTERS, v. 7, n. 5, p. 485-494, . (14/14830-8)
E SILVA, R. A.; NEGRI, R. G.; DE MATTOS VIDAL, D.. A new image-based technique for measuring pore size distribution of nonwoven geotextiles. GEOSYNTHETICS INTERNATIONAL, v. 26, n. 3, p. 261-272, . (14/14830-8)
SAPUCCI, GABRIELA RIBEIRO; NEGRI, ROGERIO GALANTE. Hierarchical clustering and stochastic distance for indirect semi-supervised remote sensing image classification. SN APPLIED SCIENCES, v. 1, n. 3, . (18/01033-3, 16/06242-4, 14/14830-8)
NEGRI, ROGERIO G.; FRERY, ALEJANDRO C.; SILVA, WAGNER B.; MENDES, TATIANA S. G.; DUTRA, LUCIANO V.. Region-based classification of PolSAR data using radial basis kernel functions with stochastic distances. INTERNATIONAL JOURNAL OF DIGITAL EARTH, v. 12, n. 6, p. 699-719, . (14/14830-8)
NEGRI, ROGERIO GALANTE; DUTRA, LUCIANO VIEIRA; FREITAS, CORINA DA COSTA; LU, DENGSHENG. Exploring the Capability of ALOS PALSAR L-Band Fully Polarimetric Data for Land Cover Classification in Tropical Environments. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, v. 9, n. 12, 1, SI, p. 5369-5384, . (07/02139-5, 14/14830-8)

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