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2020 – today
- 2024
[c31]Zhengyang Lyu, Pierre Beauseroy, Alexandre Baussard:
Study of an Expansion Method Based on an Image-Specific Classifier and Multi-Features for Weakly Supervised Semantic Segmentation. ICPRAM 2024: 402-409- 2023
- [c30]Mamadou Kanouté
, Edith Grall-Maës, Pierre Beauseroy:
Neural Network-Based Approach for Supervised Nonlinear Feature Selection. IJCCI 2023: 431-439 - 2021
- [j16]Azzam Alwan, Rémi Cogranne, Pierre Beauseroy, Edith Grall-Maës, Nicolas Belloy, Laurent Debelle, Stéphanie Baud, Manuel Dauchez, Sébastien Almagro:
A Fully Automatic and Efficient Methodology for Peptide Activity Identification Using Their 3D Conformations. IEEE Access 9: 92143-92156 (2021) - 2020
- [j15]Sofia Marino, Pierre Beauseroy, André Smolarz:
Unsupervised adversarial deep domain adaptation method for potato defects classification. Comput. Electron. Agric. 174: 105501 (2020) - [c29]Martin Palazzo, Pierre Beauseroy, Patricio Yankilevich:
Unsupervised feature selection for tumor profiles using autoencoders and kernel methods. CIBCB 2020: 1-8 - [i2]Martin Palazzo, Patricio Yankilevich, Pierre Beauseroy:
Latent regularization for feature selection using kernel methods in tumor classification. CoRR abs/2004.04866 (2020) - [i1]Martin Palazzo, Pierre Beauseroy, Patricio Yankilevich:
Unsupervised Feature Selection for Tumor Profiles using Autoencoders and Kernel Methods. CoRR abs/2007.06106 (2020)
2010 – 2019
- 2019
- [j14]Martin Palazzo, Pierre Beauseroy, Patricio Yankilevich:
A pan-cancer somatic mutation embedding using autoencoders. BMC Bioinform. 20(1): 655 (2019) - [j13]Sofia Marino, Pierre Beauseroy, André Smolarz:
Weakly-supervised learning approach for potato defects segmentation. Eng. Appl. Artif. Intell. 85: 337-346 (2019) - [c28]Sofia Marino, Pierre Beauseroy, André Smolarz:
Deep Learning-based Method for Classifying and Localizing Potato Blemishes. ICPRAM 2019: 107-117 - 2018
- [j12]Nicole Challita, Mohamad Ali Khalil, Pierre Beauseroy:
Efficiency and stability of EN-ReliefF, a new method for feature selection. Int. J. Comput. Aided Eng. Technol. 10(3): 320-339 (2018) - [j11]Patric Nader, Paul Honeine, Pierre Beauseroy:
One-Class Classification Framework Based on Shrinkage Methods. J. Signal Process. Syst. 90(3): 341-356 (2018) - [c27]Yongjian Xue, Pierre Beauseroy:
Constant False Alarm Rate for Online one Class Svm Learning. ICASSP 2018: 2821-2825 - [c26]Nicole Challita, Mohamad Ali Khalil, Pierre Beauseroy:
Efficiency of New Feature Selection Method Based on Neural Network. ICCA 2018: 317-320 - [c25]Van Khoa Le, Pierre Beauseroy, Edith Grall-Maës:
Abnormal trajectory detection for security infrastructure. ICDSP 2018: 1-5 - [c24]Yongjian Xue, Pierre Beauseroy:
Transfer Learning to Adapt One Class SVM Detection to Additional Features. ICPRAM 2018: 78-85 - [c23]Van Khoa Le, Edith Grall-Maës, Pierre Beauseroy:
Abnormal Events Detection for Infrastructure Security using Key Metrics. ICPRAM 2018: 284-290 - 2017
- [j10]Nicolas Lefebvre, Xiandong Chen, Pierre Beauseroy, Mengyao Zhu:
Traffic flow estimation using acoustic signal. Eng. Appl. Artif. Intell. 64: 164-171 (2017) - [j9]Yongjian Xue, Pierre Beauseroy:
Transfer learning for one class SVM adaptation to limited data distribution change. Pattern Recognit. Lett. 100: 117-123 (2017) - 2016
- [c22]Yongjian Xue, Pierre Beauseroy:
Multi-task learning for one-class SVM with additional new features. ICPR 2016: 1571-1576 - 2015
- [j8]Nicolas Chrysanthos, Pierre Beauseroy, Hichem Snoussi, Edith Grall-Maës:
Theoretical properties and implementation of the one-sided mean kernel for time series. Neurocomputing 169: 196-204 (2015) - [j7]Xiyan He, Pierre Beauseroy, André Smolarz:
Dynamic Feature Subspaces Selection for Decision in a Nonstationary Environment. Int. J. Pattern Recognit. Artif. Intell. 29(6): 1551009:1-1551009:24 (2015) - [c21]Patric Nader, Paul Honeine, Pierre Beauseroy:
Online One-class Classification for Intrusion Detection Based on the Mahalanobis Distance. ESANN 2015 - [c20]Patric Nader, Paul Honeine, Pierre Beauseroy:
Shrinkage methods for one-class classification. EUSIPCO 2015: 135-139 - [c19]Van Khoa Le, Pierre Beauseroy:
Path for Kernel Adaptive One-Class Support Vector Machine. ICMLA 2015: 503-508 - 2014
- [j6]Alaa Hilal, Pierre Beauseroy, Bassam Daya:
Elastic strips normalisation model for higher iris recognition performance. IET Biom. 3(4): 190-197 (2014) - [j5]Xiyan He, Gilles Mourot, Didier Maquin, José Ragot, Pierre Beauseroy, André Smolarz, Edith Grall-Maës:
Multi-task learning with one-class SVM. Neurocomputing 133: 416-426 (2014) - [j4]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) - [c18]Patric Nader, Paul Honeine, Pierre Beauseroy:
The Role of One-Class Classification in Detecting Cyberattacks in Critical Infrastructures. CRITIS 2014: 244-255 - [c17]Nicolas Chrysanthos, Pierre Beauseroy, Hichem Snoussi, Edith Grall-Maës, Fabrice Ferrand:
The one-sided mean kernel: a positive definite kernel for time series. ESANN 2014 - [c16]Patric Nader, Paul Honeine, Pierre Beauseroy:
Mahalanobis-based one-class classification. MLSP 2014: 1-6 - 2013
- [c15]Patric Nader, Paul Honeine, Pierre Beauseroy:
Intrusion detection in scada systems using one-class classification. EUSIPCO 2013: 1-5 - [c14]Alaa Hilal, Pierre Beauseroy, Bassam Daya:
Identifying Discriminatory Characteristics Location in an Iris Template. ICSS 2013: 183-193 - 2012
- [c13]Yuan Dong, Pierre Beauseroy, André Smolarz:
A robust classification method using combined classifiers in a nonstationary environment. EUSIPCO 2012: 679-683 - [c12]X. Z. Wang, Edith Grall-Maës, Pierre Beauseroy:
A Normalized Criterion of Spatial Clustering in Model-Based Framework. ICMLA (1) 2012: 542-547 - [c11]Alaa Hilal, Bassam Daya, Pierre Beauseroy:
Improved Iris Recognition using Parabolic Normalization and Multi-layer Perceptron Neural Network. IJCCI 2012: 643-646 - 2010
- [c10]Pierre Beauseroy, André Smolarz, Yuan Dong, Xiyan He:
Dynamic Decision Method Based on Contextual Selection of Representation Subspaces. ICMLA 2010: 567-572 - [c9]Xiyan He, Pierre Beauseroy, André Smolarz:
Feature subspaces selection via one-class SVM: Application to textured image segmentation. IPTA 2010: 21-25
2000 – 2009
- 2009
- [j3]Edith Grall-Maës, Pierre Beauseroy:
Optimal Decision Rule with Class-Selective Rejection and Performance Constraints. IEEE Trans. Pattern Anal. Mach. Intell. 31(11): 2073-2082 (2009) - [c8]Nisrine Jrad, Edith Grall-Maës, Pierre Beauseroy:
Gaussian Mixture Models for multiclass problems with performance constraints. ESANN 2009 - 2008
- [j2]Abdenour Bounsiar, Pierre Beauseroy, Edith Grall-Maës:
General solution and learning method for binary classification with performance constraints. Pattern Recognit. Lett. 29(10): 1455-1465 (2008) - [c7]Xiyan He, Pierre Beauseroy, André Smolarz:
Random feature subset selection in a nonstationary environment: Application to textured image segmentation. ICIP 2008: 3028-3031 - [c6]Nisrine Jrad, Edith Grall-Maës, Pierre Beauseroy:
A Supervised Decision Rule for Multiclass Problems Minimizing a Loss Function. ICMLA 2008: 48-53 - [c5]Nisrine Jrad, Edith Grall-Maës, Pierre Beauseroy:
Supervised learning rule selection for multiclass decision with performance constraints. ICPR 2008: 1-4 - [p1]Pierre Beauseroy, André Smolarz, Xiyan He:
Sélection aléatoire d'espaces de représentation pour la décision binaire en environnement non-stationnaire: application à la segmentation d'images texturées. Les Relations Spatiales 2008: 85-104 - 2006
- [c4]Edith Grall-Maës, Pierre Beauseroy, Abdenour Bounsiar:
Quality assessment of a supervised multilabel classification rule with performance constraints. EUSIPCO 2006: 1-5 - [c3]Abdenour Bounsiar, Pierre Beauseroy, Edith Grall-Maës:
Fast Training and Efficient Linear Learning Machine. ICASSP (5) 2006: 777-780 - [c2]Edith Grall-Maës, Pierre Beauseroy, Abdenour Bounsiar:
Multilabel Classification Rule with Performance Constraints. ICASSP (3) 2006: 784-787 - 2005
- [c1]Abdenour Bounsiar, Pierre Beauseroy, Edith Grall-Maës:
A straightforward SVM approach for classification with constraints. EUSIPCO 2005: 1-4 - 2002
- [j1]Edith Grall-Maës, Pierre Beauseroy:
Mutual information-based feature extraction on the time-frequency plane. IEEE Trans. Signal Process. 50(4): 779-790 (2002)
Coauthor Index
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