Shahram Hosseini

发表

Hyperspectral image unmixing by non-negative matrix factorization initialized with modified independent component analysis

Djaouad Benachir, Yannick Deville, Shahram Hosseini, 2013, 2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).

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

Yannick Deville, Shahram Hosseini, Moussa Sofiane Karoui, 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

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).

Markovian source separation

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

Simultaneous Estimation of Signal and Noise in the Constructive Neural Networks

Christian Jutten, Shahram Hosseini, C. Jutten, 1998, ICSC Symposium on Neural Computation.

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

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

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

Yannick Deville, Shahram Hosseini, Ines Meganem, 2013, 21st European Signal Processing Conference (EUSIPCO 2013).

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.

Cumulant-based estimation of quadratic mixture parameters for blind source separation

Yannick Deville, Shahram Hosseini, Chahinez Chaouchi, 2010, 2010 18th European Signal Processing Conference.

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).

Improvement of remote sensing multispectral image classification by using Independent Component Analysis

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

Semi-blind separation of galaxy spectra from a mixture obtained by slitless spectroscopy

Yannick Deville, Shahram Hosseini, Ahmed Selloum, 2015, 2015 23rd European Signal Processing Conference (EUSIPCO).

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).

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

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

Blind separation of piecewise stationary non-Gaussian sources

Yannick Deville, Shahram Hosseini, Zbynek Koldovský, 2009, Signal Process..

Effect of indirect dependencies on maximum likelihood and information theoretic blind source separation for nonlinear mixtures

Yannick Deville, Shahram Hosseini, Alain Deville, 2011, Signal Process..

Three easy ways for separating nonlinear mixtures?

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

Blind Maximum Likelihood Separation of a Linear-Quadratic Mixture

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

Blind Separation of Noisy Mixtures of Non-stationary Sources Using Spectral Decorrelation

Yannick Deville, Shahram Hosseini, Hicham Saylani, 2009, ICA.

A time-scale correlation-based blind separation method applicable to correlated sources

Hervé Carfantan, Yannick Deville, Shahram Hosseini, 2006, ESANN.

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

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

Time-domain fast fixed-point algorithms for convolutive ICA

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

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).

Colored noise in dynamic systems: unbiased modeling by constructive neural networks

Christian Jutten, Shahram Hosseini, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Weight Freezing in Constructive Neural Networks: A Novel Approach

Christian Jutten, Shahram Hosseini, 1999, IWANN.

Nonlinear Blind Source Separation Applied to a Simple Bijective Model

Yannick Deville, Shahram Hosseini, Hicham Saylani, 2012, ICISP.

A multi-tag radio-frequency identification system using a new blind source separation method based on spectral decorrelation

Shahram Hosseini, Y. Deville, Hicham Saylani, 2006 .

Markovian Blind Image Separation

Christian Jutten, Yannick Deville, Shahram Hosseini, 2006, ICA.

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

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

Fast Blind Separation of Long Mixture Recordings Using Multivariate Polynomial Identification

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

Differential Fast Fixed-Point BSS for Underdetermined Linear Instantaneous Mixtures

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

Blind identification and separation methods for Linear-Quadratic mixtures and/or linearly independent non-stationary signals

Yannick Deville, Shahram Hosseini, 2007, 2007 9th International Symposium on Signal Processing and Its Applications.

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).

Noisy cyclo-stationary BSS using frequency-domain pseudo-correlation

Yannick Deville, Shahram Hosseini, Hicham Saylani, 2010, 2010 18th European Signal Processing Conference.

Bilinear Matrix Factorization using a Gradient Method for Unmixing Hyperspectral Images Combinedc with Multispectral Data

Yannick Deville, Shahram Hosseini, Moussa Sofiane Karoui, 2018, 2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).

Separation of Stellar Spectra Based on Non-negativity and Parametric Modelling of Mixing Operator

Yannick Deville, Shahram Hosseini, Inès Meganem, 2016 .

Mixing model in slitless spectroscopy and resulting blind methods for separating galaxy spectra

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

Blind Separation of Nonstationary Markovian Sources Using an Equivariant Newton–Raphson Algorithm

Yannick Deville, Shahram Hosseini, Rima Guidara, 2009, IEEE Signal Processing Letters.

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

Yannick Deville, Shahram Hosseini, Moussa Sofiane Karoui, 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Markovian blind separation of non-stationary temporally correlated sources

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

Neural Network Modeling of Ambulatory Systolic Blood Pressure for Hypertension Diagnosis

Christian Jutten, Shahram Hosseini, Sylvie Charbonnier, 2003, IWANN.

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

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

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 unsupervised method for hyperspectral image unmixing using a linear-quadratic model

Yannick Deville, Shahram Hosseini, Ahmed Ben Hamida, 2014, 2014 1st International Conference on Advanced Technologies for Signal and Image Processing (ATSIP).

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.

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.

Recurrent networks for separating extractable-target nonlinear mixtures. Part II. Blind configurations

Yannick Deville, Shahram Hosseini, Y. Deville, 2013, Signal Process..

Blind Separation of Parametric Nonlinear Mixtures of Possibly Autocorrelated and Non-Stationary Sources

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

Blind Separation of Non-stationary Images Using Markov Models

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

Source separation algorithms for the analysis of hyper-spectral observations of very small interstellar dust particles

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

Markovian Source Separation in Post-nonlinear Mixtures

Christian Jutten, Shahram Hosseini, Anthony Larue, 2004, ICA.

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).

A multi-tag radio-frequency identification system using new blind source separation methods based on spectral decorrelation / Système d'identification radio-fréquence multi-badge utilisant de nouvelles méthodes de séparation aveugle de sources à décorrélation spectrale

Shahram Hosseini, Y. Deville, Hicham Saylani, 2007 .

Blind Operation of a Recurrent Neural Network for Linear-Quadratic Source Separation: Fixed Points, Stabilization and Adaptation Scheme

Yannick Deville, Shahram Hosseini, 2010, LVA/ICA.

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..

Blind Separation of Nonstationary Sources by Spectral Decorrelation

Yannick Deville, Shahram Hosseini, 2004, ICA.

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).

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.

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

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

Maximum likelihood neural approximation in presence of additive colored noise

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

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

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

Blind Separation of Convolutive Mixtures of Non-stationary Sources Using Joint Block Diagonalization in the Frequency Domain

Yannick Deville, Shahram Hosseini, Hicham Saylani, 2010, LVA/ICA.

A second-order blind source separation method for bilinear mixtures

Yannick Deville, Shahram Hosseini, Ahmed Ben Hamida, 2018, Multidimens. Syst. Signal Process..

Nonlinear Blind Source Separation and Blind Mixture Identification

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

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 SEPARATION OF TEMPORALLY CORRELATED SOURCES USING A QUASI MAXIMUM LIKELIHOOD APPROACH

Christian Jutten, Shahram Hosseini, Dinh Tuan Pham, 2001 .

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).

On Blind Methods in Signal Processing

Christian Jutten, Shahram Hosseini, Massoud Babaie-Zadeh, 2002 .

Maximum likelihood separation of spatially autocorrelated images using a Markov model

Christian Jutten, Yannick Deville, Shahram Hosseini, 2006 .