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ORCIDPaul Honeine
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- affiliation: Université de Rouen Normandie, France
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2020 – today
- 2024
[j52]Rosana El Jurdi
, Ahmed Rida Sekkat, Yohan Dupuis, Pascal Vasseur, Paul Honeine:
Fully residual Unet-based semantic segmentation of automotive fisheye images: a comparison of rectangular and deformable convolutions. Multim. Tools Appl. 83(13): 40269-40291 (2024)- [j51]Paul Honeine:
Theoretical insights on the pre-image resolution in machine learning. Pattern Recognit. 156: 110800 (2024) - [c80]Mohamad Dhaini, Maxime Berar, Paul Honeine, Antonin Van Exem:
Contrastive Learning for Regression on Hyperspectral Data. ICASSP 2024: 5080-5084 - [i16]Mohamad Dhaini, Maxime Berar, Paul Honeine, Antonin Van Exem:
Contrastive Learning for Regression on Hyperspectral Data. CoRR abs/2403.17014 (2024) - 2023
- [j50]Mohamad Dhaini, Maxime Berar, Paul Honeine, Antonin Van Exem:
Unsupervised domain adaptation for regression using dictionary learning. Knowl. Based Syst. 267: 110439 (2023) - [j49]Andrea Daou, Jean-Baptiste Pothin, Paul Honeine, Abdelaziz Bensrhair:
Indoor Scene Recognition Mechanism Based on Direction-Driven Convolutional Neural Networks. Sensors 23(12): 5672 (2023) - [c79]Linlin Jia, Xiao Ning, Benoit Gaüzère, Paul Honeine, Kaspar Riesen:
Bridging Distinct Spaces in Graph-Based Machine Learning. ACPR (2) 2023: 1-14 - [c78]Clément Glédel, Benoit Gaüzère, Paul Honeine:
Graph Normalizing Flows to Pre-image Free Machine Learning for Regression. GbRPR 2023: 92-101 - 2022
- [j48]Linlin Jia, Benoit Gaüzère, Paul Honeine:
Graph kernels based on linear patterns: Theoretical and experimental comparisons. Expert Syst. Appl. 189: 116095 (2022) - [j47]Ahmed Rida Sekkat, Yohan Dupuis, Varun Ravi Kumar, Hazem Rashed, Senthil Kumar Yogamani, Pascal Vasseur, Paul Honeine:
SynWoodScape: Synthetic Surround-View Fisheye Camera Dataset for Autonomous Driving. IEEE Robotics Autom. Lett. 7(3): 8502-8509 (2022) - [j46]Mohamad Dhaini, Maxime Berar, Paul Honeine, Antonin Van Exem:
End-to-End Convolutional Autoencoder for Nonlinear Hyperspectral Unmixing. Remote. Sens. 14(14): 3341 (2022) - [i15]Rosana El Jurdi, Caroline Petitjean, Veronika Cheplygina, Paul Honeine, Fahed Abdallah:
Effect of Prior-based Losses on Segmentation Performance: A Benchmark. CoRR abs/2201.02428 (2022) - [i14]Ahmed Rida Sekkat, Yohan Dupuis, Varun Ravi Kumar, Hazem Rashed, Senthil Kumar Yogamani, Pascal Vasseur, Paul Honeine:
SynWoodScape: Synthetic Surround-view Fisheye Camera Dataset for Autonomous Driving. CoRR abs/2203.05056 (2022) - 2021
- [j45]Rosana El Jurdi, Caroline Petitjean, Paul Honeine, Veronika Cheplygina, Fahed Abdallah:
High-level prior-based loss functions for medical image segmentation: A survey. Comput. Vis. Image Underst. 210: 103248 (2021) - [j44]Linlin Jia, Benoit Gaüzère, Paul Honeine:
graphkit-learn: A Python library for graph kernels based on linear patterns. Pattern Recognit. Lett. 143: 113-121 (2021) - [j43]Guillaume Renton, Muhammet Balcilar, Pierre Héroux, Benoit Gaüzère, Paul Honeine, Sébastien Adam:
Symbols Detection and Classification using Graph Neural Networks. Pattern Recognit. Lett. 152: 391-397 (2021) - [c77]Muhammet Balcilar, Guillaume Renton, Pierre Héroux, Benoit Gaüzère, Sébastien Adam, Paul Honeine:
Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective. ICLR 2021 - [c76]Muhammet Balcilar, Pierre Héroux, Benoit Gaüzère, Pascal Vasseur, Sébastien Adam, Paul Honeine:
Breaking the Limits of Message Passing Graph Neural Networks. ICML 2021: 599-608 - [c75]Rosana El Jurdi, Caroline Petitjean, Paul Honeine, Veronika Cheplygina, Fahed Abdallah:
A Surprisingly Effective Perimeter-based Loss for Medical Image Segmentation. MIDL 2021: 158-167 - [i13]Muhammet Balcilar, Pierre Héroux, Benoit Gaüzère, Pascal Vasseur, Sébastien Adam, Paul Honeine:
Breaking the Limits of Message Passing Graph Neural Networks. CoRR abs/2106.04319 (2021) - 2020
- [j42]Thi Phuong Thao Tran, Ahlame Douzal Chouakria, Saeed Varasteh Yazdi, Paul Honeine, Patrick Gallinari:
Interpretable time series kernel analytics by pre-image estimation. Artif. Intell. 286: 103342 (2020) - [j41]Yuan Liu, Stéphane Canu, Paul Honeine, Su Ruan:
Incoherent dictionary learning via mixed-integer programming and hybrid augmented Lagrangian. Digit. Signal Process. 101: 102703 (2020) - [j40]Nour El Mawass, Paul Honeine, Laurent Vercouter:
SimilCatch: Enhanced social spammers detection on Twitter using Markov Random Fields. Inf. Process. Manag. 57(6): 102317 (2020) - [j39]Rosana El Jurdi, Caroline Petitjean, Paul Honeine, Fahed Abdallah:
BB-UNet: U-Net With Bounding Box Prior. IEEE J. Sel. Top. Signal Process. 14(6): 1189-1198 (2020) - [j38]Daniel AlShamaa, Farah Mourad-Chehade, Paul Honeine, Aly Chkeir:
An Evidential Framework for Localization of Sensors in Indoor Environments. Sensors 20(1): 318 (2020) - [j37]Daniel AlShamaa, Farah Mourad-Chehade, Paul Honeine, Aly Chkeir:
Fusion of Multiple Mobility and Observation Models for Indoor Zoning-Based Sensor Tracking. IEEE Trans. Aerosp. Electron. Syst. 56(6): 4315-4326 (2020) - [c74]Fei Zhu, Paul Honeine, Jie Chen:
Pixel-Wise Linear/Nonlinear Nonnegative Matrix Factorization for Unmixing of Hyperspectral Data. ICASSP 2020: 4737-4741 - [c73]Ahmed Rida Sekkat, Yohan Dupuis, Pascal Vasseur, Paul Honeine:
The OmniScape Dataset. ICRA 2020: 1603-1608 - [c72]Rosana El Jurdi, Thomas Dargent, Caroline Petitjean, Paul Honeine, Fahed Abdallah:
Investigating CoordConv for Fully and Weakly Supervised Medical Image Segmentation. IPTA 2020: 1-5 - [c71]Linlin Jia, Benoit Gaüzère, Paul Honeine:
A Graph Pre-image Method Based on Graph Edit Distances. S+SSPR 2020: 216-226 - [c70]Linlin Jia, Benoit Gaüzère, Florian Yger, Paul Honeine:
A Metric Learning Approach to Graph Edit Costs for Regression. S+SSPR 2020: 238-247 - [i12]Muhammet Balcilar, Guillaume Renton, Pierre Héroux, Benoit Gaüzère, Sébastien Adam, Paul Honeine:
Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks. CoRR abs/2003.11702 (2020) - [i11]Daniel AlShamaa, Farah Chehade, Paul Honeine:
Statistical learning for sensor localization in wireless networks. CoRR abs/2005.05097 (2020) - [i10]Rosana El Jurdi, Caroline Petitjean, Paul Honeine, Veronika Cheplygina, Fahed Abdallah:
High-level Prior-based Loss Functions for Medical Image Segmentation: A Survey. CoRR abs/2011.08018 (2020)
2010 – 2019
- 2019
- [j36]P. J. Sudharshan, Caroline Petitjean, Fabio A. Spanhol, Luiz Eduardo Soares de Oliveira, Laurent Heutte, Paul Honeine:
Multiple instance learning for histopathological breast cancer image classification. Expert Syst. Appl. 117: 103-111 (2019) - [j35]Yuan Liu, Stéphane Canu, Paul Honeine, Su Ruan:
Mixed Integer Programming For Sparse Coding: Application to Image Denoising. IEEE Trans. Computational Imaging 5(3): 354-365 (2019) - [c69]Silvère Konlambigue, Jean-Baptiste Pothin, Paul Honeine, Abdelaziz Bensrhair:
Performance Evaluation of State-of-the-Art Filtering Criteria Applied to SIFT Features. ISSPIT 2019: 1-6 - [c68]Daniel AlShamaa, Aly Chkeir, Farah Mourad-Chehade, Paul Honeine:
A Hidden Markov Model for Indoor Trajectory Tracking of Elderly People. SAS 2019: 1-6 - 2018
- [j34]Daniel AlShamaa, Farah Mourad-Chehade, Paul Honeine:
A hierarchical classification method using belief functions. Signal Process. 148: 68-77 (2018) - [j33]Patric Nader, Paul Honeine, Pierre Beauseroy:
One-Class Classification Framework Based on Shrinkage Methods. J. Signal Process. Syst. 90(3): 341-356 (2018) - [c67]Daniel AlShamaa, Farah Mourad-Chehade, Paul Honeine:
The Belief Functions Theory for Sensors Localization in Indoor Wireless Networks. BELIEF 2018: 10-13 - [c66]Silvère Konlambigue, Jean-Baptiste Pothin, Paul Honeine, Abdelaziz Bensrhair:
Fast and Accurate Gaussian Pyramid Construction by Extended Box Filtering. EUSIPCO 2018: 400-404 - [c65]Daniel AlShamaa, Farah Mourad-Chehade, Paul Honeine:
Decentralized Sensor Localization by Decision Fusion of RSSI and Mobility in Indoor Environments. EUSIPCO 2018: 2300-2304 - [c64]Nour El Mawass, Paul Honeine, Laurent Vercouter:
Supervised Classification of Social Spammers using a Similarity-based Markov Random Field Approach. MISNC 2018: 14:1-14:8 - [c63]Yuan Liu, Stéphane Canu, Paul Honeine, Su Ruan:
K-SVD with a Real ℓ0 Optimization: Application to Image Denoising. MLSP 2018: 1-6 - [c62]Daniel AlShamaa, Farah Mourad-Chehade, Paul Honeine:
Localization of Sensors in Indoor Wireless Networks: An Observation Model Using WiFi RSS. NTMS 2018: 1-5 - [c61]Daniel AlShamaa, Farah Mourad-Chehade, Paul Honeine:
Mobility-based Tracking Using WiFi RSS in Indoor Wireless Sensor Networks. NTMS 2018: 1-5 - [c60]Daniel AlShamaa, Farah Mourad-Chehade, Paul Honeine:
A Weighted Kernel-Based Hierarchical Classification Method for Zoning of Sensors in Indoor Wireless Networks. SPAWC 2018: 1-5 - 2017
- [j32]Xi Liu, Badong Chen, Bin Xu, Zongze Wu, Paul Honeine:
Maximum correntropy unscented filter. Int. J. Syst. Sci. 48(8): 1607-1615 (2017) - [j31]Fei Zhu, Paul Honeine:
Online kernel nonnegative matrix factorization. Signal Process. 131: 143-153 (2017) - [j30]Abderrahim Halimi, Gerald S. Buller, Stephen McLaughlin, Paul Honeine:
Denoising Smooth Signals Using a Bayesian Approach: Application to Altimetry. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 10(4): 1278-1289 (2017) - [j29]Fei Zhu, Abderrahim Halimi, Paul Honeine, Badong Chen, Nanning Zheng:
Correntropy Maximization via ADMM: Application to Robust Hyperspectral Unmixing. IEEE Trans. Geosci. Remote. Sens. 55(9): 4944-4955 (2017) - [i9]Yuan Liu, Stéphane Canu, Paul Honeine, Su Ruan:
Une véritable approche $\ell_0$ pour l'apprentissage de dictionnaire. CoRR abs/1709.05937 (2017) - 2016
- [j28]Nisrine Ghadban, Paul Honeine, Farah Mourad-Chehade, Clovis Francis, Joumana Farah:
In-Network Principal Component Analysis with Diffusion Strategies. Int. J. Wirel. Inf. Networks 23(2): 97-111 (2016) - [j27]Abderrahim Halimi, Paul Honeine, Malika Kharouf, Cédric Richard, Jean-Yves Tourneret:
Estimating the Intrinsic Dimension of Hyperspectral Images Using a Noise-Whitened Eigengap Approach. IEEE Trans. Geosci. Remote. Sens. 54(7): 3811-3821 (2016) - [j26]Fei Zhu, Paul Honeine:
Biobjective Nonnegative Matrix Factorization: Linear Versus Kernel-Based Models. IEEE Trans. Geosci. Remote. Sens. 54(7): 4012-4022 (2016) - [j25]Abderrahim Halimi, Paul Honeine, José M. Bioucas-Dias:
Hyperspectral Unmixing in Presence of Endmember Variability, Nonlinearity, or Mismodeling Effects. IEEE Trans. Image Process. 25(10): 4565-4579 (2016) - [c59]Abderrahim Halimi, Gerald S. Buller, Steve McLaughlin, Paul Honeine:
Filtering smooth altimetric signals using a Bayesian algorithm. EUSIPCO 2016: 2385-2389 - [c58]Fei Zhu, Abderrahim Halimi, Paul Honeine, Badong Chen, Nanning Zheng:
ADMM for maximum correntropy criterion. IJCNN 2016: 1420-1427 - [c57]Daniel AlShamaa, Farah Mourad-Chehade, Paul Honeine:
Zoning-based localization in indoor sensor networks using belief functions theory. SPAWC 2016: 1-5 - [c56]Abderrahim Halimi, Paul Honeine, José M. Bioucas-Dias:
Robust hyperspectral unmixing accounting for residual components. SSP 2016: 1-5 - [c55]Abderrahim Halimi, Paul Honeine, José M. Bioucas-Dias, Gerald S. Buller, Steve McLaughlin:
Nonlinear hyperspectral unmixing accounting for spatial illumination variability. WHISPERS 2016: 1-5 - [i8]Fei Zhu, Abderrahim Halimi, Paul Honeine, Badong Chen, Nanning Zheng:
Correntropy Maximization via ADMM - Application to Robust Hyperspectral Unmixing. CoRR abs/1602.01729 (2016) - 2015
- [j24]Tian Wang, Jie Chen, Paul Honeine, Hichem Snoussi:
Abnormal Event Detection via Multikernel Learning for Distributed Camera Networks. Int. J. Distributed Sens. Networks 11: 989450:1-989450:9 (2015) - [j23]Sandy Mahfouz, Farah Mourad-Chehade, Paul Honeine, Joumana Farah, Hichem Snoussi:
Kernel-based machine learning using radio-fingerprints for localization in wsns. IEEE Trans. Aerosp. Electron. Syst. 51(2): 1324-1336 (2015) - [j22]Paul Honeine:
Approximation Errors of Online Sparsification Criteria. IEEE Trans. Signal Process. 63(17): 4700-4709 (2015) - [j21]Paul Honeine:
Analyzing Sparse Dictionaries for Online Learning With Kernels. IEEE Trans. Signal Process. 63(23): 6343-6353 (2015) - [c54]Patric Nader, Paul Honeine, Pierre Beauseroy:
Online One-class Classification for Intrusion Detection Based on the Mahalanobis Distance. ESANN 2015 - [c53]Fei Zhu, Paul Honeine:
Pareto front of bi-objective kernel-based nonnegative matrix factorization. ESANN 2015 - [c52]Patric Nader, Paul Honeine, Pierre Beauseroy:
Shrinkage methods for one-class classification. EUSIPCO 2015: 135-139 - [c51]Abderrahim Halimi, Nicolas Dobigeon, Jean-Yves Tourneret, Steve McLaughlin, Paul Honeine:
Unmixing multitemporal hyperspectral images accounting for endmember variability. EUSIPCO 2015: 1656-1660 - [c50]Nisrine Ghadban, Paul Honeine, Farah Mourad-Chehade, Joumana Farah, Clovis Francis:
Gossip algorithms for principal component analysis in networks. EUSIPCO 2015: 2366-2370 - [c49]Fei Zhu, Paul Honeine:
Online nonnegative matrix factorization based on kernel machines. EUSIPCO 2015: 2381-2385 - [c48]Abderrahim Halimi, Nicolas Dobigeon, Jean-Yves Tourneret, Paul Honeine:
A new Bayesian unmixing algorithm for hyperspectral images mitigating endmember variability. ICASSP 2015: 2469-2473 - [c47]Abderrahim Halimi, Nicolas Dobigeon, Jean-Yves Tourneret, Paul Honeine:
Hyperspectral unmixing accounting for spatial correlations and endmember variability. WHISPERS 2015: 1-4 - [i7]Abderrahim Halimi, Paul Honeine, Malika Kharouf, Cédric Richard, Jean-Yves Tourneret:
Estimating the Intrinsic Dimension of Hyperspectral Images Using an Eigen-Gap Approach. CoRR abs/1501.05552 (2015) - [i6]Paul Honeine, Fei Zhu:
Bi-Objective Nonnegative Matrix Factorization: Linear Versus Kernel-Based Models. CoRR abs/1501.05684 (2015) - 2014
- [j20]Jie Chen, Cédric Richard, Paul Honeine:
Nonlinear Estimation of Material Abundances in Hyperspectral Images With ℓ1-Norm Spatial Regularization. IEEE Trans. Geosci. Remote. Sens. 52(5): 2654-2665 (2014) - [j19]Patric Nader, Paul Honeine, Pierre Beauseroy:
lp-norms in One-Class Classification for Intrusion Detection in SCADA Systems. IEEE Trans. Ind. Informatics 10(4): 2308-2317 (2014) - [j18]Jie Chen, Cédric Richard, José Carlos M. Bermudez, Paul Honeine:
Variants of Non-Negative Least-Mean-Square Algorithm and Convergence Analysis. IEEE Trans. Signal Process. 62(15): 3990-4005 (2014) - [c46]Sandy Mahfouz, Paul Honeine, Farah Mourad-Chehade, Joumana Farah, Hichem Snoussi:
Combining a physical model with a nonlinear fluctuation for signal propagation modeling in WSNs. AICCSA 2014: 413-419 - [c45]Patric Nader, Paul Honeine, Pierre Beauseroy:
The Role of One-Class Classification in Detecting Cyberattacks in Critical Infrastructures. CRITIS 2014: 244-255 - [c44]Nisrine Ghadban, Paul Honeine, Clovis Francis, Farah Mourad-Chehade, Joumana Farah:
Strategies for principal component analysis in wireless sensor networks. SAM 2014: 233-236 - [c43]Sandy Mahfouz, Farah Mourad-Chehade, Paul Honeine, Joumana Farah, Hichem Snoussi:
Ridge regression and Kalman filtering for target tracking in wireless sensor networks. SAM 2014: 237-240 - [c42]Rita Ammanouil, Jean Abou Melhem, Joumana Farah, Paul Honeine:
Spectral partitioning and fusion techniques for hyperspectral data classification and unmixing. ISCCSP 2014: 550-553 - [c41]Nisrine Ghadban, Paul Honeine, Farah Mourad-Chehade, Clovis Francis, Joumana Farah:
Mobility using first and second derivatives for kernel-based regression in wireless sensor networks. IWSSIP 2014: 203-206 - [c40]Nisrine Ghadban, Paul Honeine, Farah Mourad-Chehade, Clovis Francis, Joumana Farah:
Diffusion strategies for in-network principal component analysis. MLSP 2014: 1-6 - [c39]Patric Nader, Paul Honeine, Pierre Beauseroy:
Mahalanobis-based one-class classification. MLSP 2014: 1-6 - [c38]Fei Zhu, Paul Honeine, Maya Kallas:
Kernel nonnegative matrix factorization without the pre-image problem. MLSP 2014: 1-6 - [i5]Paul Honeine:
An eigenanalysis of data centering in machine learning. CoRR abs/1407.2904 (2014) - [i4]Fei Zhu, Paul Honeine, Maya Kallas:
Kernel nonnegative matrix factorization without the curse of the pre-image. CoRR abs/1407.4420 (2014) - [i3]Paul Honeine:
Analyzing sparse dictionaries for online learning with kernels. CoRR abs/1409.6045 (2014) - [i2]Paul Honeine:
Approximation errors of online sparsification criteria. CoRR abs/1409.6046 (2014) - [i1]Paul Honeine:
Entropy of Overcomplete Kernel Dictionaries. CoRR abs/1411.0161 (2014) - 2013
- [b2]Paul Honeine:
Contributions en traitement du signal par méthodes d'apprentissage à noyaux. (Contributions to signal processing with kernel-based machine learning). University of Technology of Compiègne, France, 2013 - [j17]Maya Kallas, Paul Honeine, Cédric Richard, Clovis Francis, Hassan Amoud:
Non-negativity constraints on the pre-image for pattern recognition with kernel machines. Pattern Recognit. 46(11): 3066-3080 (2013) - [j16]Paul Honeine, Zineb Noumir, Cédric Richard:
Multiclass classification machines with the complexity of a single binary classifier. Signal Process. 93(5): 1013-1026 (2013) - [j15]Maya Kallas, Paul Honeine, Clovis Francis, Hassan Amoud:
Kernel autoregressive models using Yule-Walker equations. Signal Process. 93(11): 3053-3061 (2013) - [j14]Chafic Saidé, Régis Lengellé, Paul Honeine, Roger Achkar:
Online Kernel Adaptive Algorithms With Dictionary Adaptation for MIMO Models. IEEE Signal Process. Lett. 20(5): 535-538 (2013) - [j13]Farah Mourad, Paul Honeine, Hichem Snoussi:
Polar-Interval-Based Localization in Mobile Sensor Networks. IEEE Trans. Aerosp. Electron. Syst. 49(4): 2310-2322 (2013) - [j12]Paul Honeine, Cédric Richard, Nguyen Hoang Nguyen:
Approches géométriques pour l'estimation des fractions d'abondance en traitement de données hyperspectrales. Extensions aux modèles de mélange non linéaires. Traitement du Signal 30(1-2): 61-86 (2013) - [j11]Jie Chen, Cédric Richard, Paul Honeine:
Nonlinear Unmixing of Hyperspectral Data Based on a Linear-Mixture/Nonlinear-Fluctuation Model. IEEE Trans. Signal Process. 61(2): 480-492 (2013) - [c37]Jie Chen, Cédric Richard, José Carlos M. Bermudez, Paul Honeine:
Non-stationary analysis of the convergence of the Non-Negative Least-Mean-Square algorithm. EUSIPCO 2013: 1-5 - [c36]Paul Honeine, Henri Lantéri, Cédric Richard:
Constrained Kaczmarz's cyclic projections for unmixing hyperspectral data. EUSIPCO 2013: 1-5 - [c35]Sandy Mahfouz, Farah Mourad-Chehade, Paul Honeine, Joumana Farah, Hichem Snoussi:
Decentralized localization using fingerprinting and kernel methods inwireless sensor networks. EUSIPCO 2013: 1-5 - [c34]Patric Nader, Paul Honeine, Pierre Beauseroy:
Intrusion detection in scada systems using one-class classification. EUSIPCO 2013: 1-5 - [c33]Jie Chen, Cédric Richard, André Ferrari, Paul Honeine:
Nonlinear unmixing of hyperspectral data with partially linear least-squares support vector regression. ICASSP 2013: 2174-2178 - [c32]Sandy Mahfouz, Farah Mourad-Chehade, Paul Honeine, Hichem Snoussi, Joumana Farah:
Kernel-based localization using fingerprinting in wireless sensor networks. SPAWC 2013: 744-748 - [c31]Jie Chen, Cédric Richard, Paul Honeine:
Estimating abundance fractions of materials in hyperspectral images by fitting a post-nonlinear mixing model. WHISPERS 2013: 1-4 - [c30]Paul Honeine, Henri Lantéri:
Constrained reflect-then-combine methods for unmixing hyperspectral data. WHISPERS 2013: 1-4 - 2012
- [j10]Paul Honeine:
Online Kernel Principal Component Analysis: A Reduced-Order Model. IEEE Trans. Pattern Anal. Mach. Intell. 34(9): 1814-1826 (2012) - [j9]Paul Honeine, Cédric Richard:
Geometric Unmixing of Large Hyperspectral Images: A Barycentric Coordinate Approach. IEEE Trans. Geosci. Remote. Sens. 50(6): 2185-2195 (2012) - [c29]Zineb Noumir, Paul Honeine, Cédric Richard:
Online one-class machines based on the coherence criterion. EUSIPCO 2012: 664-668 - [c28]Maya Kallas, Paul Honeine, Cédric Richard, Clovis Francis, Hassan Amoud:
Prediction of time series using Yule-Walker equations with kernels. ICASSP 2012: 2185-2188 - [c27]Pierre-Olivier Amblard, Olivier J. J. Michel, Cédric Richard, Paul Honeine:
A Gaussian process regression approach for testing Granger causality between time series data. ICASSP 2012: 3357-3360 - [c26]Maya Kallas, Clovis Francis, Paul Honeine, Hassan Amoud, Cédric Richard:
Modeling electrocardiogram using Yule-Walker equations and kernel machines. ICT 2012: 1-5 - [c25]Maya Kallas, Clovis Francis, Lara Kanaan, Dalia Merheb, Paul Honeine, Hassan Amoud:
Multi-class SVM classification combined with kernel PCA feature extraction of ECG signals. ICT 2012: 1-5 - [c24]Farah Mourad, Paul Honeine, Hichem Snoussi:
Indoor localization using polar intervals in wireless sensor networks. ICT 2012: 1-6 - [c23]Jie Chen, Cédric Richard, Paul Honeine, Jean-Yves Tourneret:
Prediction of rain attenuation series based on discretized spectral model. IGARSS 2012: 2407-2410 - [c22]Nguyen Hoang Nguyen, Cédric Richard, Paul Honeine, Céline Theys:
Hyperspectral image unmixing using manifold learning methods derivations and comparative tests. IGARSS 2012: 3086-3089 - [c21]Zineb Noumir, Paul Honeine, Cedue Richard:
On simple one-class classification methods. ISIT 2012: 2022-2026 - [c20]Zineb Noumir, Paul Honeine, Cédric Richard:
Kernels for time series of exponential decay/growth processes. MLSP 2012: 1-6 - [c19]Zineb Noumir, Paul Honeine, Cédric Richard:
One-class machines based on the coherence criterion. SSP 2012: 600-603 - [c18]Chafic Saidé, Régis Lengellé, Paul Honeine, Cédric Richard, Roger Achkar:
Dictionary adaptation for online prediction of time series data with kernels. SSP 2012: 604-607 - [c17]Jie Chen, Cédric Richard, Paul Honeine:
Nonlinear unmixing of hyperspectral images based on multi-kernel learning. WHISPERS 2012: 1-4 - 2011
- [j8]Paul Honeine, Cédric Richard:
Preimage Problem in Kernel-Based Machine Learning. IEEE Signal Process. Mag. 28(2): 77-88 (2011) - [j7]Patrick Flandrin, Cédric Richard, Pierre-Olivier Amblard, Pierre Borgnat, Paul Honeine, Hassan Amoud, André Ferrari, Jun Xiao, Azadeh Moghtaderi, Pepa Ramírez-Cobo:
Stationnarité relative et approches connexes. Traitement du Signal 28(6): 691-716 (2011) - [j6]Jie Chen, Cédric Richard, José Carlos M. Bermudez, Paul Honeine:
Nonnegative Least-Mean-Square Algorithm. IEEE Trans. Signal Process. 59(11): 5225-5235 (2011) - [j5]Paul Honeine, Cédric Richard:
A Closed-form Solution for the Pre-image Problem in Kernel-based Machines. J. Signal Process. Syst. 65(3): 289-299 (2011) - [c16]Jie Chen, Cédric Richard, José Carlos M. Bermudez, Paul Honeine:
A modified non-negative LMS algorithm and its stochastic behavior analysis. ACSCC 2011: 542-546 - [c15]Jie Chen, Cédric Richard, Paul Honeine:
A novel kernel-based nonlinear unmixing scheme of hyperspectral images. ACSCC 2011: 1898-1902 - [c14]Maya Kallas, Paul Honeine, Cédric Richard, Clovis Francis, Hassan Amoud:
Non-negative pre-image in machine learning for pattern recognition. EUSIPCO 2011: 931-935 - [c13]Jie Chen, Cédric Richard, Henri Lantéri, Céline Theys, Paul Honeine:
Online system identification under non-negativity and ℓ1-norm constraints algorithm and weight behavior analysis. EUSIPCO 2011: 1919-1923 - [c12]Lara Kanaan, Dalia Merheb, Maya Kallas, Clovis Francis, Hassan Amoud, Paul Honeine:
PCA and KPCA of ECG signals with binary SVM classification. SiPS 2011: 344-348 - [c11]Maya Kallas, Paul Honeine, Clovis Francis, Hassan Amoud:
A comparative study of pre-image techniques: The kernel autoregressive case. SiPS 2011: 379-384 - 2010
- [j4]Paul Honeine, Cédric Richard, José Carlos M. Bermudez, Jie Chen, Hichem Snoussi:
A Decentralized Approach for Nonlinear Prediction of Time Series Data in Sensor Networks. EURASIP J. Wirel. Commun. Netw. 2010 (2010) - [j3]Pierre Borgnat, Patrick Flandrin, Paul Honeine, Cédric Richard, Jun Xiao:
Testing stationarity with surrogates: a time-frequency approach. IEEE Trans. Signal Process. 58(7): 3459-3470 (2010) - [c10]Jie Chen, Cédric Richard, Paul Honeine, Henri Lantéri, Céline Theys:
System identification under non-negativity constraints. EUSIPCO 2010: 1728-1732 - [c9]Cédric Richard, André Ferrari, Hassan Amoud, Paul Honeine, Patrick Flandrin, Pierre Borgnat:
Statistical hypothesis testing with time-frequency surrogates to check signal stationarity. ICASSP 2010: 3666-3669 - [c8]Paul Honeine, Cédric Richard:
A simple scheme for unmixing hyperspectral data based on the geometry of the N-dimensional simplex. IGARSS 2010: 2271-2274 - [c7]Paul Honeine, Cédric Richard:
The angular kernel in machine learning for hyperspectral data classification. WHISPERS 2010: 1-4
2000 – 2009
- 2009
- [j2]Cédric Richard, José Carlos M. Bermudez, Paul Honeine:
Online Prediction of Time Series Data With Kernels. IEEE Trans. Signal Process. 57(3): 1058-1067 (2009) - [c6]Paul Honeine, Cédric Richard, José Carlos M. Bermudez, Hichem Snoussi, Mehdi Essoloh, François Vincent:
Functional estimation in Hilbert space for distributed learning in wireless sensor networks. ICASSP 2009: 2861-2864 - 2008
- [c5]Paul Honeine, Cédric Richard, José Carlos M. Bermudez, Hichem Snoussi:
Distributed prediction of time series data with kernels and adaptive filtering techniques in sensor networks. ACSCC 2008: 246-250 - [c4]Mehdi Essoloh, Cédric Richard, Hichem Snoussi, Paul Honeine:
Distributed localization in wireless sensor networks as a pre-image problem in a Reproducing Kernel Hilbert Space. EUSIPCO 2008: 1-5 - [c3]Paul Honeine, Mehdi Essoloh, Cédric Richard, Hichem Snoussi:
Distributed Regression in Sensor Networks with a Reduced-Order Kernel Model. GLOBECOM 2008: 112-116 - 2007
- [b1]Paul Honeine:
Méthodes à noyau pour l'analyse et la décision en environnement non-stationnaire. (Kernel Machines for analysis and decision-making in a non-stationary environment). Ecole doctoral SSTO - UTT, Troyes, France, 2007 - [j1]Paul Honeine, Cédric Richard, Patrick Flandrin:
Time-Frequency Learning Machines. IEEE Trans. Signal Process. 55(7-2): 3930-3936 (2007) - [c2]Paul Honeine, Cédric Richard, José Carlos M. Bermudez:
On-line Nonlinear Sparse Approximation of Functions. ISIT 2007: 956-960 - 2006
- [c1]Paul Honeine, Cédric Richard, Patrick Flandrin, Jean-Baptiste Pothin:
Optimal Selection of Time-Frequency Representations for Signal Classification: a Kernel-Target Alignment Approach. ICASSP (3) 2006: 476-479
Coauthor Index
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