Ines Meganem

According to our database, Ines Meganem authored at least 8 papers between 2010 and 2017.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2017

Modified nonnegative matrix factorization for endmember spectra extraction from highly mixed hyperspectral images combined with multispectral data.

Moussa Sofiane Karoui, Shahram Hosseini, Yannick Deville, Abdelaziz Ouamri, Ines Meganem

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2014

Linear-Quadratic Blind Source Separation Using NMF to Unmix Urban Hyperspectral Images.

Ines Meganem, Yannick Deville, Shahram Hosseini, Philippe Déliot, Xavier Briottet

IEEE Trans. Signal Process., 2014

Linear-Quadratic Mixing Model for Reflectances in Urban Environments.

Ines Meganem, Philippe Déliot, Xavier Briottet, Yannick Deville, Shahram Hosseini

IEEE Trans. Geosci. Remote. Sens., 2014

2013

Positivity-based separation of stellar spectra using a parametric mixing model.

Ines Meganem, Shahram Hosseini, Yannick Deville

Proceedings of the 21st European Signal Processing Conference, 2013

2011

Extraction of stellar spectra from dense fields in hyperspectral muse data cubes using non-negative matrix factorization.

Ines Meganem, Yannick Deville, Shahram Hosseini, Hervé Carfantan, Moussa Sofiane Karoui

Proceedings of the 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2011

Physical modelling and non-linear unmixing method for urban hyperspectral images.

Ines Meganem, Philippe Déliot, Xavier Briottet, Yannick Deville, Shahram Hosseini

Proceedings of the 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2011

Linear-quadratic and polynomial Non-Negative Matrix Factorization; application to spectral unmixing.

Ines Meganem, Yannick Deville, Shahram Hosseini, Philippe Déliot, Xavier Briottet, Leonardo Tomazeli Duarte

Proceedings of the 19th European Signal Processing Conference, 2011

2010

Blind Separation methods based on correlation for sparse possibly-correlated images.

Ines Meganem, Yannick Deville, Matthieu Puigt

Proceedings of the IEEE International Conference on Acoustics, 2010