Skip to Main content Skip to Navigation
Conference papers

Pixelwise Remote Sensing Image Classification Based on Recurrence Plot Deep Features

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.
Complete list of metadata

https://hal.inrae.fr/hal-02961911
Contributor : Dominique Fournier <>
Submitted on : Thursday, October 8, 2020 - 6:45:51 PM
Last modification on : Friday, October 23, 2020 - 10:21:41 AM

Identifiers

Citation

Danielle Dias, Ulisses Dias, Nathalia Menini, Rubens Lamparelli, Guerric Le Maire, et al.. Pixelwise Remote Sensing Image Classification Based on Recurrence Plot Deep Features. IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Jul 2019, Yokohama, Japan. pp.1310-1313, ⟨10.1109/IGARSS.2019.8898128⟩. ⟨hal-02961911⟩

Share

Metrics

Record views

42