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Personal profile

External positions

Visiting Researcher, Boston University

23 Aug 201430 Jun 2015

Keywords

  • Q Science (General)
  • machine learning
  • deep learning
  • remote sensing
  • video processing
  • image processing

Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

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Research Output 2005 2019

A new fully convolutional neural network for semantic segmentation of polarimetric SAR imagery in complex land cover ecosystem

Mohammadimanesh, F., Salehi, B., Mahdianpari, M., Gill, E. & Molinier, M., 2019, In : ISPRS Journal of Photogrammetry and Remote Sensing. 151, p. 223-236 14 p.

Research output: Contribution to journalArticleResearchpeer-review

radar imagery
semantics
ecosystems
synthetic aperture radar
Synthetic aperture radar

Comparison of Sentinel-2 and Landsat 8 imagery for forest variable prediction in boreal region

Astola, H., Häme, T., Sirro, L., Molinier, M. & Kilpi, J., 15 Mar 2019, In : Remote Sensing of Environment. 223, p. 257-273 17 p.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
Landsat
imagery
prediction
Mean square error
stem
10 Citations (Scopus)

Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

Anwer, R. M., Khan, F. S., van de Weijer, J., Molinier, M. & Laaksonen, J., 1 Apr 2018, In : ISPRS Journal of Photogrammetry and Remote Sensing. 138, p. 74–85 12 p.

Research output: Contribution to journalArticleResearchpeer-review

remote sensing
Remote sensing
textures
Textures
texture

Deepcloud - A Fully Convolutionnal Neural Network for Cloud and Shadow Masking in Optical Satellite Images

Molinier, M., Reunanen, N., Lämsä, A., Astola, H. & Räty, T., 5 Nov 2018, 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings. Institute of Electrical and Electronic Engineers IEEE, p. 2107-2110 4 p. 8517484

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsResearchpeer-review

detection method
automation
Landsat
learning
satellite image
1 Citation (Scopus)

Landsat time series analysis for temperate forest cover change detection in the Sierra Madre Occidental, Durango, Mexico

Novo-Fernández, A., Franks, S., Wehenkel, C., López-Serrano, P. M., Molinier, M. & López-Sánchez, C. A., 2 Jul 2018, In : International Journal of Applied Earth Observation and Geoinformation. 73, p. 230-244 15 p.

Research output: Contribution to journalArticleResearchpeer-review

Time series analysis
time series analysis
temperate forest
forest cover
Landsat