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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.)

Fusion of time series representations for plant recognition in phenology studies

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Author(s):
Faria, Fabio A. ; Almeida, Jurandy ; Alberton, Bruna ; Morellato, Leonor Patricia C. ; Torres, Ricardo da S.
Total Authors: 5
Document type: Journal article
Source: PATTERN RECOGNITION LETTERS; v. 83, n. 2, p. 205-214, NOV 1 2016.
Web of Science Citations: 7
Abstract

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)

FAPESP's process: 14/00215-0 - Remote phenology and leaf exchange patterns towards a sazonality gradient
Grantee:Bruna de Costa Alberton
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 10/51307-0 - Floristic diversity and seasonal patterns of rupestrian fields and cerrado
Grantee:Leonor Patricia Cerdeira Morellato
Support type: Research Grants - Research Partnership for Technological Innovation - PITE
FAPESP's process: 13/50169-1 - Towards an understanding of tipping points within tropical South American biomes
Grantee:Ricardo da Silva Torres
Support type: Research Grants - Research Partnership for Technological Innovation - PITE
FAPESP's process: 09/18438-7 - Large-scale classification and retrieval for complex data
Grantee:Ricardo da Silva Torres
Support type: Regular Research Grants
FAPESP's process: 10/52113-5 - e-phenology: the application of new technologies to monitor plant phenology and track climate changes in the tropics
Grantee:Leonor Patricia Cerdeira Morellato
Support type: Research Program on Global Climate Change - Regular 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)