DuPLO: A DUal view Point deep Learning architecture for time series classificatiOn-Reference-Cited by-同舟云学术

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DuPLO: A DUal view Point deep Learning architecture for time series classificatiOn

Published:2019-03 Issue: Volume:149 Page:91-104
ISSN:0924-2716
Container-title:ISPRS Journal of Photogrammetry and Remote Sensing
language:en
Short-container-title:ISPRS Journal of Photogrammetry and Remote Sensing

Author:

Interdonato Roberto^ORCID,Ienco Dino,Gaetano Raffaele,Ose Kenji

Funder

French National Research Agency

Programme National de Télédétection Spatiale

French Ministry of agriculture

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Computer Science Applications,Engineering (miscellaneous),Atomic and Molecular Physics, and Optics

Reference52 articles.

1. Comparative analysis of modis time-series classification using support vector machines and methods based upon distance and similarity measures in the Brazilian Cerrado-Caatinga boundary;Abade;Remote Sens.,2015

2. Remote sensing and cropping practices: a review;Bégué;Remote Sens.,2018

3. A remote sensing approach for regional-scale mapping of agricultural land-use systems based on NDVI time series;Bellón;Remote Sens.,2017

4. Benedetti, P., Ienco, D., Gaetano, R., Ose, K., Pensa, R.G., Dupuy, S., 2018. M3fusion: A deep learning architecture for multi-{Scale/Modal/Temporal} satellite data fusion. CoRR abs/1803.01945.

5. Representation learning: a review and new perspectives;Bengio;IEEE TPAMI,2013

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