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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A Multirepresentational Fusion of Time Series for Pixelwise Classification

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Author(s):
Dias, Danielle [1] ; Pinto, Allan [2] ; Dias, Ulisses [3] ; Lamparelli, Rubens [4] ; Le Maire, Guerric [5] ; Torres, Ricardo da S. [6]
Total Authors: 6
Affiliation:
[1] Univ Campinas Unicamp, Inst Comp, BR-13083852 Campinas - Brazil
[2] Univ Campinas Unicamp, Sch Phys Educ, Inst Comp, BR-13083851 Campinas - Brazil
[3] Univ Campinas Unicamp, Sch Technol, BR-13484332 Limeira - Brazil
[4] Univ Estadual Campinas, Nucleo Interdisciplinar Planejamento Energetico, BR-13083896 Campinas - Brazil
[5] Univ Montpellier, Montpellier SupAgro, Eco&Sols, CIRAD, INRA, IRD, F-34060 Montpellier 2 - France
[6] Norwegian Univ Sci & Technol, Dept ICT & Nat Sci, NO-6009 Alesund - Norway
Total Affiliations: 6
Document type: Journal article
Source: IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING; v. 13, p. 4399-4409, 2020.
Web of Science Citations: 0
Abstract

This article addresses the pixelwise classification problem based on temporal profiles, which are encoded in 2-D representations based on recurrence plots, Gramian angular/ difference fields, and Markov transition field. We propose a multirepresentational fusion scheme that exploits the complementary view provided by those time series representations and different data-driven feature extractors and classifiers. We validate our ensemble scheme in the problem related to the classification of eucalyptus plantations in remote sensing images. Achieved results demonstrate that our proposal overcomes recently proposed baselines, and now represents the new state-of-the-art classification solution for the target dataset. (AU)

FAPESP's process: 19/16253-1 - Unraveling the secret of Brazilian and Dutch soccer by capturing successful elements of playing style and playing strategies
Grantee:Allan da Silva Pinto
Support type: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 16/50250-1 - The secret of playing football: Brazil versus the Netherlands
Grantee:Sergio Augusto Cunha
Support type: 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 type: 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 type: Multi-user Equipment Program
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 type: Research Projects - Thematic Grants
FAPESP's process: 13/50155-0 - Combining new technologies to monitor phenology from leaves to ecosystems
Grantee:Leonor Patricia Cerdeira Morellato
Support type: Research Program on Global Climate Change - University-Industry Cooperative Research (PITE)
FAPESP's process: 15/24494-8 - Communications and processing of big data in cloud and fog computing
Grantee:Nelson Luis Saldanha da Fonseca
Support type: Research Projects - Thematic Grants