If you made any changes in Pure these will be visible here soon.

Personal profile

Biography

Charlotte Pelletier has recently joined the machine learning team at the Faculty of Information Technology at Monash University in Melbourne, Australia. Her postdoctoral, supervised by Pr. Geoff Webb and Dr. François Petitjean, mainly focuses on the scalability of time series classification algorithms. 

In December 2017, she completed her Ph.D. with the French Space Agency (CNES) and the French Mapping Agency (IGN), at CESBIO laboratory in Toulouse (France). She worked under the supervision of Pr. Gérard Dedieu (CNES) and Dr. Silvia Valero (Associate Professor at the University of Toulouse). Her Ph.D work aimed at improving the classification of new high resolution satellite image time series, such as the Sentinel-2 one. In particular, she analyzed the classifier robustness to the presence of mislabeled training data. She also explored the use of mislabeled data detection techniques, and she proposed new filtering approaches to deal with mislabeled data in the classification framework. 

In 2014, she received her electrical engineering degree from ENSEIRB-MATMECA/INP in Bordeaux (France) and her master degree from Université Bordeaux (France). 

Keywords

  • Machine Learning
  • Image Processing
  • Outlier Detection
  • Time Series Classification
  • Data Analysis
  • Remote Sensing
  • Satellite Images
  • Random Forests (RF)
  • Support Vector Machines (SVM)

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2015 2017

  • 5 Conference Paper
  • 3 Article

Detection of irrigated crops from Sentinel-1 and Sentinel-2 data to estimate seasonal groundwater use in South India

Ferrant, S., Selles, A., Le Page, M., Herrault, P. A., Pelletier, C., Al-Bitar, A., Mermoz, S., Gascoin, S., Bouvet, A., Saqalli, M., Dewandel, B., Caballero, Y., Ahmed, S., Maréchal, J. C. & Kerr, Y. H., 3 Nov 2017, In : Remote Sensing. 9, 11, 21 p., 1119.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File

Effect of training class label noise on classification performances for land cover mapping with satellite image time series

Pelletier, C., Valero, S., Inglada, J., Champion, N., Sicre, C. M. & Dedieu, G., 18 Feb 2017, In : Remote Sensing. 9, 2, 24 p., 173.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File

Filtering mislabeled data for improving time series classification

Pelletier, C., Valero, S., Inglada, J., Dedieu, G. & Champion, N., 2017, 2017 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp 2017): Brugge, Belgium 27-29 June 2017. Swinnen, E. & De Lannoy, G. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 4 p. 8035217

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

New iterative learning strategy to improve classification systems by using outlier detection techniques

Pelletier, C., Valero, S., Inglada, J., Dedieu, G. & Champion, N., 2017, 2017 IEEE International Geoscience & Remote Sensing Symposium - Proceedings: July 23–28, 2017 Fort Worth, Texas, USA. T. Johnson, J. & Chen, K-S. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 3676-3679 4 p. 8127796

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

An assessment of image features and random forest for land cover mapping over large areas using high resolution Satellite Image Time Series

Pelletier, C., Valero, S., Inglada, J., Dedieu, G. & Champion, N., 2016, 2016 IEEE International Geoscience and Remote Sensing Symposium - Proceedings: July 10–15, 2016 Beijing, China. Shi, J., Guo, H. & Chen, K. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 3338-3341 4 p. 7729863

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch