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Mohand Saïd Allili
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- affiliation: Université du Québec en Outaouais, Canada
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2020 – today
- 2025
- [j24]Yassine Bouafia, Mohand Saïd Allili, Loucif Hebbache, Larbi Guezouli:
SES-ReNet: Lightweight deep learning model for human detection in hazy weather conditions. Signal Process. Image Commun. 130: 117223 (2025) - 2024
- [j23]Adama Nouboukpo
, Mohamed Lamine Allaoui
Multi-scale spatial consistency for deep semi-supervised skin lesion segmentation. Eng. Appl. Artif. Intell. 135: 108681 (2024) - [j22]Dariush Amirkhani
Visual Concrete Bridge Defect Classification and Detection Using Deep Learning: A Systematic Review. IEEE Trans. Intell. Transp. Syst. 25(9): 10483-10505 (2024) - [c40]Mohamed Lamine Allaoui, Mohand Saïd Allili:
MEDiXNet: A Robust Mixture of Expert Dermatological Imaging Networks for Skin Lesion Segmentation. ISBI 2024: 1-5 - [i2]Asal Rouhafzay, Nadia Baaziz, Mohand Saïd Allili:
Texture image retrieval using a classification and contourlet-based features. CoRR abs/2403.06048 (2024) - 2023
- [j21]Loucif Hebbache
Leveraging Saliency in Single-Stage Multi-Label Concrete Defect Detection Using Unmanned Aerial Vehicle Imagery. Remote. Sens. 15(5): 1218 (2023) - [j20]Daniel Yapi
Mixture of multivariate generalized Gaussians for multi-band texture modeling and representation. Signal Process. 209: 109011 (2023) - 2022
- [c39]Sakineh Abdollahzadeh, Pier-Luc Proulx, Mohand Saïd Allili, Jean-François Lapointe
Safe Landing Zones Detection for UAVs Using Deep Regression. CRV 2022: 213-218 - [c38]Jean-François Lapointe
AI-AR for Bridge Inspection by Drone. HCI (17) 2022: 302-313 - [c37]Daniel Yapi
Multi-Band Texture Modeling Using Finite Mixtures of Multivariate Generalized Gaussian Distributions. ICPR 2022: 464-469 - 2021
- [c36]Adama Nouboukpo
Weakly Semi Supervised learning based Mixture Model With Two-Level Constraints. FLAIRS 2021 - 2020
- [j19]Nadjate Saidani, Kamel Adi, Mohand Saïd Allili:
A semantic-based classification approach for an enhanced spam detection. Comput. Secur. 94: 101716 (2020) - [j18]Ouiza Ouyed, Mohand Saïd Allili:
Group-of-features relevance in multinomial kernel logistic regression and application to human interaction recognition. Expert Syst. Appl. 148: 113247 (2020) - [c35]Hicham Messaoudi
Efficient Embedding Network for 3D Brain Tumor Segmentation. BrainLes@MICCAI (1) 2020: 252-262 - [c34]Jean-François Lapointe
A Literature Review of AR-Based Remote Guidance Tasks with User Studies. HCI (11) 2020: 111-120 - [i1]Hicham Messaoudi, Ahror Belaid, Mohamed Lamine Allaoui, Ahcene Zetout, Mohand Saïd Allili, Souhil Tliba, Douraied Ben Salem, Pierre-Henri Conze:
Efficient embedding network for 3D brain tumor segmentation. CoRR abs/2011.11052 (2020)
2010 – 2019
- 2019
- [j17]Mohand Saïd Allili, Nathalie Casemajor
Multiple image copy detection and evolution visualisation using tree graphs. Multim. Tools Appl. 78(5): 6253-6275 (2019) - [j16]Lakhdar Laib, Mohand Saïd Allili, Samy Ait-Aoudia:
A probabilistic topic model for event-based image classification and multi-label annotation. Signal Process. Image Commun. 76: 283-294 (2019) - [c33]Nadjate Saidani, Kamel Adi, Mohand Saïd Allili:
Semantic Representation Based on Deep Learning for Spam Detection. FPS 2019: 72-81 - [c32]Adama Nouboukpo, Mohand Saïd Allili:
Spatially-Coherent Segmentation Using Hierarchical Gaussian Mixture Reduction Based on Cauchy-Schwarz Divergence. ICIAR (1) 2019: 388-396 - 2018
- [j15]Ouiza Ouyed, Mohand Saïd Allili:
Feature weighting for multinomial kernel logistic regression and application to action recognition. Neurocomputing 275: 1752-1768 (2018) - [j14]Daniel Yapi
Automatic Fabric Defect Detection Using Learning-Based Local Textural Distributions in the Contourlet Domain. IEEE Trans Autom. Sci. Eng. 15(3): 1014-1026 (2018) - [j13]Aissa Boulmerka
Foreground Segmentation in Videos Combining General Gaussian Mixture Modeling and Spatial Information. IEEE Trans. Circuits Syst. Video Technol. 28(6): 1330-1345 (2018) - [c31]Karim Tabia, Mohand Saïd Allili:
Special Track on Uncertain Reasoning. FLAIRS 2018: 506 - [c30]Ouiza Ouyed, Mohand Saïd Allili:
Recognizing Human Interactions Using Group Feature Relevance in Multinomial Kernel Logistic Regression. FLAIRS 2018: 541-546 - 2017
- [c29]Mohand Saïd Allili, Siham Bacha:
Feature Relevance in Bayesian Network Classifiers and Application to Image Event Recognition. FLAIRS 2017: 760-763 - [c28]François Audet, Mohand Saïd Allili, Ana-Maria Cretu:
Salient Object Detection in Images by Combining Objectness Clues in the RGBD Space. ICIAR 2017: 247-255 - [c27]Nadjate Saidani, Kamel Adi, Mouhand Saïd Allili:
A Supervised Approach for Spam Detection Using Text-Based Semantic Representation. MCETECH 2017: 136-148 - 2016
- [j12]Siham Bacha, Mohand Saïd Allili, Nadjia Benblidia
Event recognition in photo albums using probabilistic graphical models and feature relevance. J. Vis. Commun. Image Represent. 40: 546-558 (2016) - [j11]Idir Filali
Multi-scale salient object detection using graph ranking and global-local saliency refinement. Signal Process. Image Commun. 47: 380-401 (2016) - [c26]Idir Filali
Multi-graph Based Salient Object Detection. ICIAR 2016: 318-324 - [c25]Siham Bacha, Mohand Saïd Allili, Nadjia Benblidia
Event recognition in photo albums using probabilistic graphical model and feature relevance. ICPR 2016: 2819-2823 - 2015
- [j10]Mohand Saïd Allili, Djemel Ziou:
Likelihood-based feature relevance for figure-ground segmentation in images and videos. Neurocomputing 167: 658-670 (2015) - [c24]Aissa Boulmerka
Background modeling in videos revisited using finite mixtures of generalized Gaussians and spatial information. ICIP 2015: 3660-3664 - 2014
- [j9]Aissa Boulmerka
A generalized multiclass histogram thresholding approach based on mixture modelling. Pattern Recognit. 47(3): 1330-1348 (2014) - [j8]Mohand Saïd Allili, Nadia Baaziz, Marouene Mejri:
Texture Modeling Using Contourlets and Finite Mixtures of Generalized Gaussian Distributions and Applications. IEEE Trans. Multim. 16(3): 772-784 (2014) - [c23]Ouiza Ouyed, Mohand Saïd Allili:
Feature Relevance for Kernel Logistic Regression and Application to Action Classification. ICPR 2014: 1325-1329 - 2012
- [j7]Mohand Saïd Allili:
Wavelet Modeling Using Finite Mixtures of Generalized Gaussian Distributions: Application to Texture Discrimination and Retrieval. IEEE Trans. Image Process. 21(4): 1452-1464 (2012) - [c22]Guillaume Larivière, Mohand Saïd Allili:
A Learning Probabilistic Approach for Object Segmentation. CRV 2012: 86-93 - [c21]Aissa Boulmerka, Mohand Saïd Allili:
Thresholding-based segmentation revisited using mixtures of generalized Gaussian distributions. ICPR 2012: 2894-2897 - 2011
- [c20]Mohand Saïd Allili, Nadia Baaziz:
Contourlet-Based Texture Retrieval Using a Mixture of Generalized Gaussian Distributions. CAIP (2) 2011: 446-454 - [c19]Pablo Julian Pedrocca, Mohand Saïd Allili:
Real-Time People Detection in Videos Using Geometrical Features and Adaptive Boosting. ICIAR (1) 2011: 314-324 - [c18]Madjid Allili, Donglei Li, Mouhand Saïd Allili:
A digital topology-based method for the topological filtering of a reconstructed surface. Visualization and Data Analysis 2011: 78680U - 2010
- [j6]Mohand Saïd Allili, Djemel Ziou, Nizar Bouguila, Sabri Boutemedjet:
Image and Video Segmentation by Combining Unsupervised Generalized Gaussian Mixture Modeling and Feature Selection. IEEE Trans. Circuits Syst. Video Technol. 20(10): 1373-1377 (2010) - [c17]Mohand Saïd Allili, Djemel Ziou, Nizar Bouguila, Sabri Boutemedjet:
Unsupervised Feature Selection and Learning for Image Segmentation. CRV 2010: 285-292 - [c16]Mohand Saïd Allili:
Wavelet-Based Texture Retrieval Using a Mixture of Generalized Gaussian Distributions. ICPR 2010: 3143-3146
2000 – 2009
- 2009
- [c15]Mohand Saïd Allili:
Object Contour Tracking Using Foreground and Background Distribution Matching. CIARP 2009: 954-961 - [c14]Mohand Saïd Allili:
Effective object tracking by matching object and background models using active contours. ICIP 2009: 873-876 - 2008
- [j5]Mohand Saïd Allili, Djemel Ziou:
Object tracking in videos using adaptive mixture models and active contours. Neurocomputing 71(10-12): 2001-2011 (2008) - [j4]Mohand Saïd Allili, Nizar Bouguila, Djemel Ziou:
Finite general Gaussian mixture modeling and application to image and video foreground segmentation. J. Electronic Imaging 17(1): 013005 (2008) - [c13]Mohand Saïd Allili, Djemel Ziou:
An approach for dynamic combination of region and boundary information in segmentation. ICPR 2008: 1-4 - 2007
- [j3]Mohand Saïd Allili, Djemel Ziou:
Automatic colour-texture image segmentation using active contours. Int. J. Comput. Math. 84(9): 1325-1338 (2007) - [j2]Mohand Saïd Allili, Djemel Ziou:
Globally adaptive region information for automatic color-texture image segmentation. Pattern Recognit. Lett. 28(15): 1946-1956 (2007) - [j1]Mohand Saïd Allili, Djemel Ziou:
Active contours for video object tracking using region, boundary and shape information. Signal Image Video Process. 1(2): 101-117 (2007) - [c12]Mohand Saïd Allili, Nizar Bouguila, Djemel Ziou:
Finite Generalized Gaussian Mixture Modeling and Applications to Image and Video Foreground Segmentation. CRV 2007: 183-190 - [c11]Mohand Saïd Allili, Djemel Ziou:
Using Feature Selection For Object Segmentation and Tracking. CRV 2007: 191-200 - [c10]Mohand Saïd Allili, Nizar Bouguila, Djemel Ziou:
A Robust Video Foreground Segmentation by Using Generalized Gaussian Mixture Modeling. CRV 2007: 503-509 - [c9]Mohand Saïd Allili, Djemel Ziou:
Adaptive Appearance Model for Object Contour Tracking in Videos. CRV 2007: 510-518 - [c8]Mohand Saïd Allili, Djemel Ziou:
Object of Interest segmentation and Tracking by Using Feature Selection and Active Contours. CVPR 2007 - 2006
- [c7]Mohand Saïd Allili, Djemel Ziou:
Object Contour Tracking in Videos by Matching Finite Mixture Models. AVSS 2006: 35 - [c6]Mohand Saïd Allili, Djemel Ziou:
Object contour tracking in videos by using adaptive mixture models and shape priors. CompIMAGE 2006: 47-52 - [c5]Mohand Saïd Allili, Djemel Ziou:
A Robust Video Object Tracking by Using Active Contours. CVPR Workshops 2006: 135 - [c4]Mohand Saïd Allili, Djemel Ziou:
Automatic Color-Texture Image Segmentation by Using Active Contours. IWICPAS 2006: 495-504 - 2005
- [c3]Mohand Saïd Allili, Djemel Ziou:
A Bayesian Approach for Weighting Boundary and Region Information for Segmentation. ACIVS 2005: 468-475 - [c2]Mohand Saïd Allili, Djemel Ziou:
An Automatic Segmentation Combining Mixture Analysis and Adaptive Region Information: A Level Set Approach. CRV 2005: 73-80 - [c1]Mohand Saïd Allili, Djemel Ziou:
An automatic segmentation of color images by using a combination of mixture modelling and adaptive region information: a level set approach. ICIP (1) 2005: 305-308
Coauthor Index
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