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Riadh Ksantini
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2020 – today
- 2025
- [j32]Amal Shaheen
, Nairouz Mrabah, Riadh Ksantini, Abdulla Alqaddoumi:
Rethinking deep clustering paradigms: Self-supervision is all you need. Neural Networks 181: 106773 (2025) - 2024
- [j31]Yusuf Mothanna, Wael Elmedany
Adopting security practices in software development process: Security testing framework for sustainable smart cities. Comput. Secur. 144: 103985 (2024) - [j30]Dorra Zaibi, Riadh Ksantini, Meriem Riahi, Faouzi Moussa:
Toward a CNN-based approach for usability requirements generation. Int. J. Appl. Decis. Sci. 17(4): 411-433 (2024) - [j29]Boujemaa Guermazi, Riadh Ksantini, Naimul Khan:
DynaSeg: A deep dynamic fusion method for unsupervised image segmentation incorporating feature similarity and spatial continuity. Image Vis. Comput. 150: 105206 (2024) - [j28]Nairouz Mrabah
A contrastive variational graph auto-encoder for node clustering. Pattern Recognit. 149: 110209 (2024) - [c43]Mohamed Amine Ouali, Mohamed Bouguessa, Riadh Ksantini:
DfHM: A Hierarchical Approach for Matching Pairs of Images Using Graph Attention Neural Networks. IJCNN 2024: 1-10 - 2023
- [j27]Soumaya Nheri, Riadh Ksantini, Mohamed Bécha Kaâniche
Exploiting scatter matrix on one-class support vector machine based on low variance direction. Intell. Data Anal. 27(6): 1663-1679 (2023) - [j26]Marwa Fouda
A Novel Intrusion Detection System for Internet of Healthcare Things Based on Deep Subclasses Dispersion Information. IEEE Internet Things J. 10(10): 8395-8407 (2023) - [j25]Safa Mefteh
A novel multispectral corner detector and a new local descriptor: an application to human posture recognition. Multim. Tools Appl. 82(19): 28937-28956 (2023) - [j24]Haifa Jammeli
Sequential Artificial Intelligence Models to Forecast Urban Solid Waste in the City of Sousse, Tunisia. IEEE Trans. Engineering Management 70(5): 1912-1922 (2023) - [j23]Nairouz Mrabah
Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering. IEEE Trans. Knowl. Data Eng. 35(9): 9037-9053 (2023) - [c42]Marwa Salhi, Riadh Ksantini, Belhassen Zouari
Deep Interactive Volume Exploration Through Pre-Trained 3D CNN and Active Learning. VISIGRAPP (1: GRAPP) 2023: 170-178 - [c41]Safa Mefteh
Learning Human Postures Using Lab-Depth HOG Descriptors. ICCCI 2023: 552-564 - [c40]Nairouz Mrabah, Mohamed Bouguessa, Riadh Ksantini:
Adversarial Deep Embedded Clustering: On a better trade-off between Feature Randomness and Feature Drift (Extended abstract). ICDE 2023: 3887-3888 - [c39]Nairouz Mrabah, Mohamed Bouguessa, Mohamed Fawzi Touati, Riadh Ksantini:
Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering (Extended abstract). ICDE 2023: 3891-3892 - [c38]Marwa Ben Ammar, Faten Labbene Ayachi, Riadh Ksantini, Halima Mahjoubi:
Pre-Trained Deep Convolutional Neural Network Architectures for Breast Cancer Diagnosis in Mammography: Current State-Of-The-Art. INISTA 2023: 1-7 - [c37]Nairouz Mrabah, Mohamed Bouguessa, Riadh Ksantini:
Beyond The Evidence Lower Bound: Dual Variational Graph Auto-Encoders For Node Clustering. SDM 2023: 100-108 - [i8]Nairouz Mrabah, Mohamed Bouguessa, Riadh Ksantini:
A Contrastive Variational Graph Auto-Encoder for Node Clustering. CoRR abs/2312.16830 (2023) - 2022
- [j22]Taha Elamine Hadjadj
Optimization of parallel firewalls filtering rules. Int. J. Inf. Sec. 21(2): 323-340 (2022) - [j21]Marwa Salhi, Riadh Ksantini, Belhassen Zouari:
A real-time image-centric transfer function design based on incremental classification. J. Real Time Image Process. 19(1): 185-203 (2022) - [j20]Zahra Mohamed, Riadh Ksantini, Jihene Kaabi
Convolutional dynamic auto-encoder: a clustering method for semantic images. Neural Comput. Appl. 34(19): 17087-17105 (2022) - [j19]Elham Eskandarnia
Deep Learning Techniques for Smart Meter Data Analytics: A Review. SN Comput. Sci. 3(3): 243 (2022) - [j18]Nairouz Mrabah
Adversarial Deep Embedded Clustering: On a Better Trade-off Between Feature Randomness and Feature Drift. IEEE Trans. Knowl. Data Eng. 34(4): 1603-1617 (2022) - [c36]Boujemaa Guermazi, Riadh Ksantini, Naimul Khan:
A Dynamically Weighted Loss Function for Unsupervised Image Segmentation. BigMM 2022: 73-78 - [c35]Mohamed Amine Ouali, Mohamed Bouguessa, Riadh Ksantini:
Graph Attention Network for Camera Relocalization on Dynamic Scenes. DSAA 2022: 1-10 - [c34]Marwa Salhi, Riadh Ksantini, Belhassen Zouari
Detection of Breast Masses in Mammograms by Incremental Discriminant Based Support Vector Machine Classifier and Active User Involvement. ICCCI (CCIS Volume) 2022: 373-384 - [c33]Nairouz Mrabah
Escaping Feature Twist: A Variational Graph Auto-Encoder for Node Clustering. IJCAI 2022: 3351-3357 - [i7]Mohamed Amine Ouali, Mohamed Bouguessa, Riadh Ksantini:
Graph Attention Network for Camera Relocalization on Dynamic Scenes. CoRR abs/2209.15056 (2022) - 2021
- [c32]Marwa Ben Ammar, Faten Labbene Ayachi, Riadh Ksantini, Halima Mahjoubi:
Data warehouse for machine learning: application to breast cancer diagnosis. CENTERIS/ProjMAN/HCist 2021: 692-698 - [i6]Nairouz Mrabah, Mohamed Bouguessa, Mohamed Fawzi Touati, Riadh Ksantini:
Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering. CoRR abs/2107.08562 (2021) - 2020
- [j17]Arbia Soula, Khaoula Tbarki
A novel incremental Kernel Nonparametric SVM model (iKN-SVM) for data classification: An application to face detection. Eng. Appl. Artif. Intell. 89: 103468 (2020) - [j16]Nairouz Mrabah
Deep clustering with a Dynamic Autoencoder: From reconstruction towards centroids construction. Neural Networks 130: 206-228 (2020) - [c31]Noureddine Amraoui, Amine Besrour, Riadh Ksantini, Belhassen Zouari:
Securing Smart Homes using a Behavior Analysis based Authentication Approach. COMNET 2020: 1-5 - [c30]Ahmed Zgaren
Coarse-to-Fine Object Tracking Using Deep Features and Correlation Filters. ISVC (1) 2020: 517-529 - [c29]Yves Nsoga Nguimbous, Riadh Ksantini, Adel Bouhoula:
A Low Inertia Guided Auto-Encoder for Anomaly Detection in Networks. SoftCOM 2020: 1-6 - [c28]Soumaya Nheri, Riadh Ksantini, Mohamed Bécha Kaâniche
A Novel Dispersion Covariance-guided One-Class Support Vector Machines. VISIGRAPP (4: VISAPP) 2020: 546-553 - [i5]Ahmed Zgaren, Wassim Bouachir, Riadh Ksantini:
Coarse-to-Fine Object Tracking Using Deep Features and Correlation Filters. CoRR abs/2012.12784 (2020)
2010 – 2019
- 2019
- [j15]Amine Besrour
Incremental Subclass Support Vector Machine. Int. J. Artif. Intell. Tools 28(7): 1950020:1-1950020:22 (2019) - [j14]Arbia Soula, Salma Ben Said, Riadh Ksantini, Zied Lachiri:
An Adaptive Face Recognition System Based on a Novel Incremental Kernel Nonparametric Discriminant Analysis. KSII Trans. Internet Inf. Syst. 13(4): 2129-2147 (2019) - [j13]Takoua Kefi-Fatteh
A novel incremental one-class support vector machine based on low variance direction. Pattern Recognit. 91: 308-321 (2019) - [j12]Takoua Kefi-Fatteh
Human face detection improvement using incremental learning based on low variance directions. Signal Image Video Process. 13(8): 1503-1510 (2019) - [c27]Noureddine Amraoui, Amine Besrour, Riadh Ksantini, Belhassen Zouari:
Implicit and Continuous Authentication of Smart Home Users. AINA 2019: 1228-1239 - [c26]Taha Elamine Hadjadj, Rim Tebourbi, Adel Bouhoula, Riadh Ksantini:
Optimization of Parallel Firewalls Filtering Rules. SoftCOM 2019: 1-6 - [c25]Yves Nsoga Nguimbous, Riadh Ksantini, Adel Bouhoula:
Anomaly-based Intrusion Detection Using Auto-encoder. SoftCOM 2019: 1-5 - [c24]Safa Mefteh
A Novel Multispectral Lab-depth based Edge Detector for Color Images with Occluded Objects. VISIGRAPP (4: VISAPP) 2019: 272-279 - [i4]Nairouz Mrabah, Naimul Mefraz Khan, Riadh Ksantini:
Deep Clustering with a Dynamic Autoencoder. CoRR abs/1901.07752 (2019) - [i3]Nairouz Mrabah, Mohamed Bouguessa, Riadh Ksantini:
Adversarial Deep Embedded Clustering: on a better trade-off between Feature Randomness and Feature Drift. CoRR abs/1909.11832 (2019) - 2018
- [j11]Naimul Mefraz Khan
A Novel Image-Centric Approach Toward Direct Volume Rendering. ACM Trans. Intell. Syst. Technol. 9(4): 42:1-42:18 (2018) - [c23]Yosr Ben Youssef, Mériem Afif, Riadh Ksantini, Sami Tabbane:
A Novel Online QoE Prediction Model Based on Multiclass Incremental Support Vector Machine. AINA 2018: 334-341 - [c22]Arbia Soula, Salma Ben Said, Riadh Ksantini, Zied Lachiri:
A novel incremental face recognition method based on nonparametric discriminant model. ATSIP 2018: 1-6 - [c21]Soumaya Nheri, Riadh Ksantini, Mouhamed Bécha Kaâniche
A Novel Handwritten Digits Recognition Method based on Subclass Low Variances Guided Support Vector Machine. VISIGRAPP (4: VISAPP) 2018: 28-36 - [c20]Yosr Ben Youssef, Mériem Afif, Riadh Ksantini, Sami Tabbane:
A novel QoE model based on boosting support vector regression. WCNC 2018: 1-6 - 2017
- [c19]Takoua Kefi, Riadh Ksantini, Mohamed Bécha Kaâniche
Human Face Detection Improvement Using Incremental Learning Based on Low Variance Directions. ACIVS 2017: 170-179 - [c18]Khaoula Tbarki
Landmine detection improvement using one-class SVM for unbalanced data. ATSIP 2017: 1-6 - [c17]Khaoula Tbarki
One-class SVM for landmine detection and discrimination. ICCAD 2017: 309-313 - [c16]Arbia Soula, Riadh Ksantini, Salma Ben Said, Zied Lachiri:
A novel face recognition system base on nonparametric discriminant analysis. ICCAD 2017: 343-348 - [i2]Naimul Mefraz Khan, Riadh Ksantini, Ling Guan:
A Novel Image-centric Approach Towards Direct Volume Rendering. CoRR abs/1711.11123 (2017) - 2016
- [c15]Khaoula Tbarki
RBF kernel based SVM classification for landmine detection and discrimination. IPAS 2016: 1-6 - [c14]Takoua Kefi, Riadh Ksantini, Mohamed Bécha Kaâniche
A Novel Incremental Covariance-Guided One-Class Support Vector Machine. ECML/PKDD (2) 2016: 17-32 - [i1]Takoua Kefi, Riadh Ksantini, Mohamed Bécha Kaâniche
Incremental One-Class Models for Data Classification. CoRR abs/1610.04725 (2016) - 2015
- [c13]Riadh Ksantini, Raouf Gharbi:
A Novel Kernelized Classifier Based on the Combination of Partially Global and Local Characteristics. LWA 2015: 181-192 - 2014
- [j10]Naimul Mefraz Khan, Riadh Ksantini, Imran Shafiq Ahmad, Ling Guan:
Covariance-guided One-Class Support Vector Machine. Pattern Recognit. 47(6): 2165-2177 (2014) - [j9]Naimul Mefraz Khan, Riadh Ksantini, Imran Shafiq Ahmad, Ling Guan:
SN-SVM: a sparse nonparametric support vector machine classifier. Signal Image Video Process. 8(8): 1625-1637 (2014) - [c12]Naimul Mefraz Khan, Riadh Ksantini, Ling Guan:
Volume visualization using sparse nonparametric support vector machines and harmoniccolors. ICASSP 2014: 6607-6611 - [c11]Sara Memar, Riadh Ksantini, Boubakeur Boufama:
Multiple Object Detection with Occlusion Using Active Contour Model and Fuzzy C-Mean. ICIAR (1) 2014: 224-233 - 2013
- [j8]Riadh Ksantini, Boubakeur Boufama, Sara Memar:
A new efficient active contour model without local initializations for salient object detection. EURASIP J. Image Video Process. 2013: 40 (2013) - [c10]Naimul Mefraz Khan, Riadh Ksantini, Imran Shafiq Ahmad, Ling Guan:
Incorporating covariance information in one class support vector classification. ICASSP 2013: 3552-3556 - 2012
- [j7]Riadh Ksantini, Boubakeur Boufama:
Combining partially global and local characteristics for improved classification. Int. J. Mach. Learn. Cybern. 3(2): 119-131 (2012) - [j6]Naimul Mefraz Khan, Riadh Ksantini, Imran Shafiq Ahmad, Boubakeur Boufama:
A novel SVM+NDA model for classification with an application to face recognition. Pattern Recognit. 45(1): 66-79 (2012) - [c9]Naimul Mefraz Khan, Riadh Ksantini, Imran Shafiq Ahmad, Ling Guan:
A Sparse Support Vector Machine Classifier with Nonparametric Discriminants. ICANN (2) 2012: 330-338 - 2011
- [j5]Riadh Ksantini, Boubakeur Boufama, Imran Shafiq Ahmad:
A New KSVM + KFD Model for Improved Classification and Face Recognition. J. Multim. 6(1): 39-47 (2011) - 2010
- [j4]Riadh Ksantini, Boubakeur Boufama, Djemel Ziou, Bernard Colin:
A novel Bayesian logistic discriminant model: An application to face recognition. Pattern Recognit. 43(4): 1421-1430 (2010) - [c8]Abdunnaser Diaf, Rachid Benlamri, Boubakeur Boufama, Riadh Ksantini:
A novel eigenspace-based method for human action recognition. ICDIM 2010: 182-187 - [c7]Riadh Ksantini, Boubakeur Boufama, Imran Shafiq Ahmad, Naimul Mefraz Khan:
A new combined KSVM and KFD model for classification and recognition. ICDIM 2010: 188-193 - [c6]Naimul Mefraz Khan, Riadh Ksantini, Imran Shafiq Ahmad, Boubakeur Boufama:
A New SVM + NDA Model for Improved Classification and Recognition. ICIAR (1) 2010: 127-136 - [c5]Abdunnaser Diaf, Riadh Ksantini, Boubakeur Boufama, Rachid Benlamri:
A Novel Human Motion Recognition Method Based on Eigenspace. ICIAR (1) 2010: 167-175
2000 – 2009
- 2009
- [c4]Riadh Ksantini, Farnaz Shariat, Boubakeur Boufama:
An Efficient and Fast Active Contour Model for Salient Object Detection. CRV 2009: 124-131 - [c3]Riadh Ksantini, Boubakeur Boufama:
A Novel Bayesian Logistic Discriminant Model with Dirichlet Distributions: An Application to Face Recognition. ICIAR 2009: 461-470 - 2008
- [j3]Riadh Ksantini, Djemel Ziou, Bernard Colin, François Dubeau:
Weighted Pseudometric Discriminatory Power Improvement Using a Bayesian Logistic Regression Model Based on a Variational Method. IEEE Trans. Pattern Anal. Mach. Intell. 30(2): 253-266 (2008) - [c2]Riadh Ksantini, Djemel Ziou, Bernard Colin, François Dubeau:
A Bayesian Kernel Logistic Discriminant Model: An Improvement to the Kernel Fisher's Discriminant. AAAI 2008: 1464-1465 - 2007
- [c1]Riadh Ksantini, Djemel Ziou, Bernard Colin, François Dubeau:
Logistic Regression Models for a Fast CBIR Method Based on Feature Selection. IJCAI 2007: 2790-2795 - 2006
- [j2]Riadh Ksantini, Djemel Ziou, François Dubeau:
Image Retrieval Based on Region Separation and Multiresolution Analysis. Int. J. Wavelets Multiresolution Inf. Process. 4(1): 147-175 (2006) - 2004
- [j1]François Dubeau, Said Elmejdani, Riadh Ksantini:
Non-uniform Haar wavelets. Appl. Math. Comput. 159(3): 675-693 (2004)
Coauthor Index
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last updated on 2024-10-23 20:23 CEST by the dblp team
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