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ORCIDMohamed Limam
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2020 – today
- 2021
[j21]Dhouha Mejri
, Mohamed Limam, Claus Weihs:
A new time adjusting control limits chart for concept drift detection. IFAC J. Syst. Control. 17: 100170 (2021)
2010 – 2019
- 2019
- [j20]Fatma Hachmi, Khadouja Boujenfa, Mohamed Limam:
Enhancing the Accuracy of Intrusion Detection Systems by Reducing the Rates of False Positives and False Negatives Through Multi-objective Optimization. J. Netw. Syst. Manag. 27(1): 93-120 (2019) - 2018
- [j19]Afef Ben Brahim, Mohamed Limam:
Ensemble feature selection for high dimensional data: a new method and a comparative study. Adv. Data Anal. Classif. 12(4): 937-952 (2018) - [j18]Dhouha Mejri, Mohamed Limam, Claus Weihs:
A new dynamic weighted majority control chart for data streams. Soft Comput. 22(2): 511-522 (2018) - [c25]Imèn Khanchouch, Mohamed Limam:
Adapting a Multi-SOM Clustering Algorithm to Large Banking Data. WorldCIST (1) 2018: 171-181 - 2017
- [j17]Haïfa Nakouri, Mohamed Limam:
Incremental robust principal component analysis for face recognition using ridge regression. Int. J. Biom. 9(3): 186-204 (2017) - [c24]Mohamed Limam, Frédéric Precioso:
AF Detection and ECG Classification based on Convolutional Recurrent Neural Network. CinC 2017 - [c23]Haïfa Nakouri, Mhamed-Ali El-Aroui, Mohamed Limam:
Robust Low-Rank Approximation of Images for Background and Foreground Separation. PDCAT 2017: 196-203 - 2016
- [j16]Afef Ben Brahim, Mohamed Limam:
A hybrid feature selection method based on instance learning and cooperative subset search. Pattern Recognit. Lett. 69: 28-34 (2016) - [c22]Haïfa Nakouri, Mohamed Limam:
Robust Generalized Low Rank Approximation of Matrices for image recognition. ISSPIT 2016: 203-207 - [c21]Haïfa Nakouri, Mohamed Limam:
An Incremental Two-Dimensional Principal Component Analysis for Image Compression and Recognition. SITIS 2016: 725-731 - 2015
- [j15]Chiheb-Eddine Ben N'cir, Nadia Essoussi, Mohamed Limam:
Kernel-Based Methods to Identify Overlapping Clusters with Linear and Nonlinear Boundaries. J. Classif. 32(2): 176-211 (2015) - [j14]Fatma Hachmi, Khadouja Boujenfa, Mohamed Limam:
An optimization process to identify outliers generated by intrusion detection systems. Secur. Commun. Networks 8(18): 3469-3480 (2015) - [c20]Fatma Hachmi, Khadouja Boujenfa, Mohamed Limam:
A Three-Stage Process to Detect Outliers and False Positives Generated by Intrusion Detection Systems. CIT/IUCC/DASC/PICom 2015: 1749-1755 - [c19]Fatma Hachmi, Mohamed Limam:
A Two-Stage Process Based on Data Mining and Optimization to Identify False Positives and False Negatives Generated by Intrusion Detection Systems. CIS 2015: 308-311 - [c18]Afef Ben Brahim, Mohamed Limam:
Sequential Instance Based Feature Subset Selection for High Dimensional Data. MIKE 2015: 37-46 - [c17]Fatma Hachmi, Mohamed Limam:
An Improved Intrusion Detection System Based on a Two Stage Alarm Correlation to Identify Outliers and False Alerts. MIKE 2015: 130-139 - 2014
- [c16]Afef Ben Brahim, Mohamed Limam:
A Stable Instance Based Filter for Feature Selection in Small Sample Size Data Sets. ADMA 2014: 334-344 - [c15]Dhouha Mejri, Mohamed Limam, Claus Weihs:
Monitoring a Dynamic Weighted Majority Method Based on Datasets with Concept Drift. ECDA 2014: 241-250 - [c14]Haïfa Nakouri, Mohamed Limam:
Discovering Multi-sense Features from Images Using Random Indexing. ICAISC (1) 2014: 733-744 - [c13]Haïfa Nakouri, Mohamed Limam:
Automatic Feature Detection and Clustering Using Random Indexing. ICISP 2014: 586-593 - [c12]Haïfa Nakouri, Mohamed Limam:
Discovering Features Contexts from Images Using Random Indexing. IWCIA 2014: 134-145 - [c11]Afef Ben Brahim, Mohamed Limam:
New prior knowledge based extensions for stable feature selection. SoCPaR 2014: 306-311 - [c10]Waad Bouaguel, Mohamed Limam:
An Ensemble Wrapper Feature Selection for Credit Scoring. SocProS (1) 2014: 619-631 - 2013
- [j13]Bouaguel Waad, Ghazi Bel Mufti, Mohamed Limam:
A Three-Stage Feature Selection using quadratic Programming for Credit Scoring. Appl. Artif. Intell. 27(8): 721-742 (2013) - [j12]Haïfa Nakouri, Mohamed Limam:
A New Bilinear Approach for Incremental Visual Learning and Recognition. Int. J. Pattern Recognit. Artif. Intell. 27(5) (2013) - [j11]Haïfa Nakouri, Mohamed Limam:
Erratum: "a New Bilinear Approach for Incremental Visual Learning and Recognition". Int. J. Pattern Recognit. Artif. Intell. 27(7) (2013) - [j10]Walid Gani, Mohamed Limam:
Performance Evaluation of One-Class Classification-based Control Charts through an Industrial Application. Qual. Reliab. Eng. Int. 29(6): 841-854 (2013) - [c9]Bouaguel Waad, Afef Ben Brahim, Mohamed Limam:
Feature Selection by Rank Aggregation and Genetic Algorithms. KDIR/KMIS 2013: 74-81 - [c8]Afef Ben Brahim, Mohamed Limam:
Robust ensemble feature selection for high dimensional data sets. HPCS 2013: 151-157 - [c7]Bouaguel Waad, Ghazi Bel Mufti, Mohamed Limam:
Rank Aggregation for Filter Feature Selection in Credit Scoring. MIKE 2013: 7-15 - [c6]Bouaguel Waad, Ghazi Bel Mufti, Mohamed Limam:
Similarity Aggregation a New Version of Rank Aggregation Applied to Credit Scoring Case. MIKE 2013: 618-628 - [c5]Haïfa Nakouri, Mohamed Limam:
Extension of Robust Principal Component Analysis for Incremental Face Recognition. VISAPP (1) 2013: 549-555 - 2012
- [j9]Ghaith Manita, Riadh Khanchel, Mohamed Limam:
Consensus Functions for Cluster Ensembles. Appl. Artif. Intell. 26(6): 598-614 (2012) - [j8]Issam Ben Khediri, Claus Weihs, Mohamed Limam:
Kernel k-means clustering based local support vector domain description fault detection of multimodal processes. Expert Syst. Appl. 39(2): 2166-2171 (2012) - 2011
- [j7]Ben Khediri Issam, Mohamed Limam, Claus Weihs:
Variable window adaptive Kernel Principal Component Analysis for nonlinear nonstationary process monitoring. Comput. Ind. Eng. 61(3): 437-446 (2011) - [j6]Fedya Telmoudi, Mohamed El Ghourabi, Mohamed Limam:
RST-GCBR-Clustering-Based RGA-SVM Model for Corporate Failure Prediction. Intell. Syst. Account. Finance Manag. 18(2-3): 105-120 (2011) - [j5]Walid Gani, Hassen Taleb, Mohamed Limam:
An assessment of the kernel-distance-based multivariate control chart through an industrial application. Qual. Reliab. Eng. Int. 27(4): 391-401 (2011) - [c4]Sondes Fayech, Nadia Essoussi, Mohamed Limam:
DM-pred Method: A New Method to Predict Secondary Structures Based on Data Mining Techniques. DEXA Workshops 2011: 445-449 - 2010
- [c3]Afef Ben Brahim, Riadh Khanchel, Mohamed Limam:
Solving data fusion problems using robust classifiers combination. SoCPaR 2010: 303-308
2000 – 2009
- 2009
- [j4]Sondes Fayech, Nadia Essoussi, Mohamed Limam:
Partitioning clustering algorithms for protein sequence data sets. BioData Min. 2 (2009) - [j3]Imen Kooli, Mohamed Limam:
Bayesian np control charts with adaptive sample size for finite production runs. Qual. Reliab. Eng. Int. 25(4): 439-448 (2009) - 2008
- [j2]Ben Khediri Issam, Mohamed Limam:
Support vector regression based residual MCUSUM control chart for autocorrelated process. Appl. Math. Comput. 201(1-2): 565-574 (2008) - 2006
- [j1]Naim Zbidi, Sami Faïz, Mohamed Limam:
On Mining Summaries by Objective Measures of Interestingness. Mach. Learn. 62(3): 175-198 (2006) - 2005
- [c2]Hassen Taleb, Mohamed Limam:
Fuzzy Multinomial Control Charts. AI*IA 2005: 553-563 - 2004
- [c1]Riadh Khanchel, Mohamed Limam:
Empirical Comparison of Boosting Algorithms. GfKl 2004: 161-167
Coauthor Index
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