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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Fusion of time series representations for plant recognition in phenology studies

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Autor(es):
Faria, Fabio A. ; Almeida, Jurandy ; Alberton, Bruna ; Morellato, Leonor Patricia C. ; Torres, Ricardo da S.
Número total de Autores: 5
Tipo de documento: Artigo Científico
Fonte: PATTERN RECOGNITION LETTERS; v. 83, n. 2, p. 205-214, NOV 1 2016.
Citações Web of Science: 6
Resumo

Nowadays, global warming and its resulting environmental changes is a hot topic in different biology research area. Phenology is one effective way of tracking such environmental changes through the study of plant's periodic events and their relationship to climate. One promising research direction in this area relies on the use of vegetation images to track phenology changes over time. In this scenario, the creation of effective image-based plant identification systems is of paramount importance. In this paper, we propose the use of a new representation of time series to improve plants recognition rates. This representation, called recurrence plot (RP), is a technique for nonlinear data analysis, which represents repeated events on time series into a two-dimensional representation (an image). Therefore, image descriptors can be used to characterize visual properties from this RP images so that these features can be used as input of a classifier. To the best of our knowledge, this is the first work that uses recurrence plot for plant recognition task. Performed experiments show that RP can be a good solution to describe time series. In addition, in a comparison with visual rhythms (VR), another technique used for time series representation, RP shows a better performance to describe texture properties than VR. On the other hand, a correlation analysis and the adoption of a well successful classifier fusion framework show that both representations provide complementary information that is useful for improving classification accuracies. (C) 2016 Elsevier B.V. All rights reserved. (AU)

Processo FAPESP: 14/00215-0 - Fenologia remota e os padrões de trocas foliares ao longo de um gradiente de sazonalidade
Beneficiário:Bruna de Costa Alberton
Linha de fomento: Bolsas no Brasil - Doutorado
Processo FAPESP: 10/51307-0 - Diversidade florística e padrões sazonais dos campos rupestres e cerrado
Beneficiário:Leonor Patricia Cerdeira Morellato
Linha de fomento: Auxílio à Pesquisa - Parceria para Inovação Tecnológica - PITE
Processo FAPESP: 13/50169-1 - Towards an understanding of tipping points within tropical South American biomes
Beneficiário:Ricardo da Silva Torres
Linha de fomento: Auxílio à Pesquisa - Parceria para Inovação Tecnológica - PITE
Processo FAPESP: 13/50155-0 - Combining new technologies to monitor phenology from leaves to ecosystems
Beneficiário:Leonor Patricia Cerdeira Morellato
Linha de fomento: Auxílio à Pesquisa - Programa de Pesquisa sobre Mudanças Climáticas Globais - PITE
Processo FAPESP: 10/52113-5 - E-fenologia: aplicação de novas tecnologias para monitorar a fenologia e mudanças climáticas nos trópicos
Beneficiário:Leonor Patricia Cerdeira Morellato
Linha de fomento: Auxílio à Pesquisa - Programa de Pesquisa sobre Mudanças Climáticas Globais - Regular
Processo FAPESP: 09/18438-7 - Classificação e busca em grande escala para dados complexos
Beneficiário:Ricardo da Silva Torres
Linha de fomento: Auxílio à Pesquisa - Regular