S. Hosseini

Yannick Deville, Shahram Hosseini, Moussa Sofiane Karoui, 2009, 2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing.

Fast Blind Separation of Long Mixture Recordings Using Multivariate Polynomial Identification

Yannick Deville, Shahram Hosseini, Johan Thomas, 2008, IEEE Transactions on Signal Processing.

Contribution of non-negative matrix factorization to the classification of remote sensing images

Moussa Sofiane Karoui, Y. Deville, D. Ducrot, 2008, Remote Sensing.

Extension of EFICA algorithm for blind separation of piecewise stationary non Gaussian sources

Yannick Deville, Shahram Hosseini, Zbynek Koldovský, 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

Three easy ways for separating nonlinear mixtures?

Christian Jutten, Shahram Hosseini, Massoud Babaie-Zadeh, 2004, Signal Process..

Markovian source separation

Dinh-Tuan Pham, Christian Jutten, Shahram Hosseini, 2003, IEEE Trans. Signal Process..

Spatially-Weighted Factor Analysis for Extraction of Source-Oriented Mineralization Feature in 3D Coordinates of Surface Geochemical Signal

S. H. Tabatabaei, Y. Deville, S. Hosseini, 2021, Natural Resources Research.

Stable Higher-Order Recurrent Neural Network Structures for Nonlinear Blind Source Separation

Yannick Deville, Shahram Hosseini, Y. Deville, 2007, ICA.

Blind Maximum Likelihood Separation of a Linear-Quadratic Mixture

Yannick Deville, Shahram Hosseini, Y. Deville, 2004, ICA.

Blind Separation of Linear-Quadratic Mixtures of Real Sources Using a Recurrent Structure

Yannick Deville, Shahram Hosseini, Y. Deville, 2009, IWANN.

Maximum Likelihood Blind Image Separation Using Nonsymmetrical Half-Plane Markov Random Fields

Yannick Deville, Shahram Hosseini, Rima Guidara, 2009, IEEE Transactions on Image Processing.

Blind spatial unmixing of multispectral images: New methods combining sparse component analysis, clustering and non-negativity constraints

Yannick Deville, Shahram Hosseini, Moussa Sofiane Karoui, 2012, Pattern Recognit..

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

Yannick Deville, Shahram Hosseini, Xavier Briottet, 2014, IEEE Transactions on Signal Processing.

Differential Fast Fixed-Point Algorithms for Underdetermined Instantaneous and Convolutive Partial Blind Source Separation

Yannick Deville, Shahram Hosseini, Johan Thomas, 2007, IEEE Transactions on Signal Processing.

Time-domain fast fixed-point algorithms for convolutive ICA

Yannick Deville, Shahram Hosseini, Johan Thomas, 2006, IEEE Signal Processing Letters.

Differential Fast Fixed-Point BSS for Underdetermined Linear Instantaneous Mixtures

Yannick Deville, Shahram Hosseini, Johan Thomas, 2006, ICA.

Recurrent networks for separating extractable-target nonlinear mixtures. Part I: Non-blind configurations

Yannick Deville, Shahram Hosseini, Y. Deville, 2009, Signal Process..

Nonlinear Blind Source Separation and Blind Mixture Identification

Yannick Deville, Shahram Hosseini, Leonardo Tomazeli Duarte, 2021 .

Linear–Quadratic Mixing Model for Reflectances in Urban Environments

Yannick Deville, Shahram Hosseini, Xavier Briottet, 2014, IEEE Transactions on Geoscience and Remote Sensing.

A New Separation Method for Galaxy Spectra Based on Data Fusion between Two Grism Orders in Slitless Spectroscopy

Yannick Deville, Shahram Hosseini, Thierry Contini, 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

A Blind Source Separation Method Based on Output Nonlinear Correlation for Bilinear Mixtures

Yannick Deville, Shahram Hosseini, Andréa Guerrero, 2018, LVA/ICA.

A map-based NMF approach to hyperspectral image unmixing using a linear-quadratic mixture model

Yannick Deville, Shahram Hosseini, Ahmed Ben Hamida, 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Blind spatial unmixing of multispectral images: An approach based on two-source sparsity and geometrical properties

Djaouad Benachir, Yannick Deville, Shahram Hosseini, 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Modified independent component analysis for initializing non-negative matrix factorization: An approach to hyperspectral image unmixing

Djaouad Benachir, Yannick Deville, Shahram Hosseini, 2013, 2013 IEEE 11th International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics.

Blind unmixing of remote sensing data with some pure pixels: Extension and comparison of spatial methods exploiting sparsity and nonnegativity properties

Yannick Deville, Shahram Hosseini, Moussa Sofiane Karoui, 2013, 2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA).

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

Hervé Carfantan, Yannick Deville, Shahram Hosseini, 2011, 2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).

Spatial sparsity-based blind source separation method including non-negative matrix factorization for multispectral image unmixing

M. S. Karoui, Y. Deville, S. Hosseini, 2011, 2011 10th International Workshop on Electronics, Control, Measurement and Signals.

Separation of galaxy spectra measured with slitless spectroscopy

Yannick Deville, Ahmed Selloum, Shahram Hosseini, 2020, Digit. Signal Process..

Improving neural network estimation in presence of non i.i.d. noise

Christian Jutten, Shahram Hosseini, C. Jutten, 1998, The European Symposium on Artificial Neural Networks.

Maximum likelihood neural approximation in presence of additive colored noise

Christian Jutten, Shahram Hosseini, C. Jutten, 2002, IEEE Trans. Neural Networks.

Extending NMF to blindly separate linear-quadratic mixtures of uncorrelated sources

Yannick Deville, Shahram Hosseini, Leonardo Tomazeli Duarte, 2016, 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP).

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

Yannick Deville, Shahram Hosseini, Xavier Briottet, 2011, 2011 19th European Signal Processing Conference.

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

Yannick Deville, Shahram Hosseini, Xavier Briottet, 2011, 2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).

Blind Source Separation of Spectrally Filtered Geochemical Signals to Recognize Multi-depth Ore-Related Enrichment Patterns

S. H. Tabatabaei, Y. Deville, S. Hosseini, 2023, Mathematical Geosciences.

Blind separation of linear instantaneous mixtures of non-stationary signals in the frequency domain

Yannick Deville, Shahram Hosseini, Hicham Saylani, 2009, Signal Process..

Blind Unmixing of Hyperspectral Remote Sensing Data: A New Geometrical Method Based on a Two-Source Sparsity Constraint

Djaouad Benachir, Yannick Deville, Moussa Sofiane Karoui, 2020, Remote. Sens..

A new multiplicative nonnegative matrix factorization method for unmixing hyperspectral images combined with multispectral data

Yannick Deville, Shahram Hosseini, Moussa Sofiane Karoui, 2017, 2017 25th European Signal Processing Conference (EUSIPCO).

A new spatial sparsity-based method for extracting endmember spectra from hyperspectral data with some pure pixels

M. S. Karoui, Y. Deville, S. Hosseini, 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

Markovian blind separation of non-stationary temporally correlated sources

Yannick Deville, Shahram Hosseini, Rima Guidara, 2007, ESANN.