Biblio

18 resultats trouvés
Filtres: Mot-clé is semi-supervised learning  [Clear All Filters]
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Dornaika F., Y. Traboulsi E, Ruicheck Y..  2019.  Active Two Phase Collaborative Representation Classifier for Image Categorization. IMAGE ANALYSIS AND PROCESSING - ICIAP 2019, PT I. 11751:175-184.
Adal KM, Sidibe D, Ali S, Chaum E, Karnowski TP, Meriaudeau F.  2014.  Automated detection of microaneurysms using scale-adapted blob analysis and semi-adapted blob analysis and semi-supervised learning. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. 114
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Zhu R, Dornaika F, Ruichek Y.  2019.  Discriminant Manifold Learning with Graph Convolution Based Regression for Image Classification. GRAPH-BASED REPRESENTATIONS IN PATTERN RECOGNITION, GBRPR 2019. 11510:226-236.
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Zhu R., Dornaika F., Ruichek Y..  2018.  Flexible and Discriminative Non-linear Embedding with Feature Selection for Image Classification. 2018 24TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR). :3192-3197.
Zhu R., Dornaika F., Ruichek Y..  2018.  Flexible and Discriminative Non-linear Embedding with Feature Selection for Image Classification. 2018 24TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR). :3192-3197.
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Dornaika F., Bosaghzadeh A., Salmane H., Ruichek Y..  2014.  A graph construction method using LBP self-representativeness for outdoor object categorization. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE. 36:294-302.
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Zhu R, Dornaika F, Ruichek Y.  2021.  Inductive semi-supervised learning with Graph Convolution based regression. NEUROCOMPUTING. 434:315-322.
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Zhu R, Dornaika F, Ruichek Y.  2019.  Joint Graph Based Embedding and Feature Weighting for Image Classification. 2019 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN).
Zhu R, Dornaika F, Ruichek Y.  2019.  Joint graph based embedding and feature weighting for image classification. PATTERN RECOGNITION. 93:458-469.
Zhu R, Dornaika F, Ruichek Y.  2019.  Joint Graph Based Embedding and Feature Weighting for Image Classification. 2019 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN).
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Zhu R, Dornaika F, Ruichek Y.  2019.  Learning a discriminant graph-based embedding with feature selection for image categorization. NEURAL NETWORKS. 111:35-46.
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Dornaika F, Dhabi R, Ruichek Y, Bosaghzadeh A.  2017.  Recognizing Multiple Observations Using Adaptive Graph Based Label Propagation. 2017 3RD INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION AND IMAGE ANALYSIS (IPRIA). :200-205.
Dornaika F, Dhabi R, Ruichek Y, Bosaghzadeh A.  2017.  Recognizing Multiple Observations Using Adaptive Graph Based Label Propagation. 2017 3RD INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION AND IMAGE ANALYSIS (IPRIA). :200-205.
Dornaika F., Y. Traboulsi E, Zhu R..  2018.  Robust and Flexible Graph-based Semi-supervised Embedding. 2018 24TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR). :465-470.
Dornaika F., Y. Traboulsi E, Zhu R..  2018.  Robust and Flexible Graph-based Semi-supervised Embedding. 2018 24TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR). :465-470.
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Zhu R., Dornaika F., Ruichek Y..  2020.  Semi-supervised elastic manifold embedding with deep learning architecture. PATTERN RECOGNITION. 107:107425.
Y. Traboulsi E, Dornaika F., Ruichek Y..  2018.  Semi-supervised two phase test sample sparse representation classifier. KNOWLEDGE-BASED SYSTEMS. 160:16-27.
Qian W, Lauri F, Gechter F.  2021.  Supervised and semi-supervised deep probabilistic models for indoor positioning problems. NEUROCOMPUTING. 435:228-238.