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PIXELWISE REMOTE SENSING IMAGE CLASSIFICATION BASED ON RECURRENCE PLOT DEEP FEATURES

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Author(s):
Dias, Danielle ; Dias, Ulisses ; Menini, Nathalia ; Lamparelli, Rubens ; Le Maire, Guerric ; Torres, Ricardo ; IEEE
Total Authors: 7
Document type: Journal article
Source: 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019); v. N/A, p. 4-pg., 2019-01-01.
Abstract

Pixelwise remote sensing image classification has benefited from temporal contextual information encoded in time series. In this paper, we investigate the use of data-driven features extracted from time series representations based on recurrence plots, with the goal of improving the effectiveness of classification systems. Performed experiments considered the classification of eucalyptus plantations based on time series profiles. Achieved results demonstrate that the combination of recurrence plot representations with deep-learning features are a promising research venue for addressing pixelwise classification problems. (AU)

FAPESP's process: 13/50155-0 - Combining new technologies to monitor phenology from leaves to ecosystems
Grantee:Leonor Patricia Cerdeira Morellato
Support Opportunities: Research Program on Global Climate Change - University-Industry Cooperative Research (PITE)
FAPESP's process: 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction?
Grantee:Alexandre Xavier Falcão
Support Opportunities: Research Projects - Thematic Grants
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Grantee:Sergio Augusto Cunha
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FAPESP's process: 15/24494-8 - Communications and processing of big data in cloud and fog computing
Grantee:Nelson Luis Saldanha da Fonseca
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 14/50715-9 - Characterizing and predicting biomass production in sugarcane and eucalyptus plantations in Brazil
Grantee:Rubens Augusto Camargo Lamparelli
Support Opportunities: Research Grants - Research Partnership for Technological Innovation - PITE
FAPESP's process: 17/20945-0 - Multi-user equipment approved in great 16/50250-1: local positioning system
Grantee:Sergio Augusto Cunha
Support Opportunities: Multi-user Equipment Program