Souad CHAABOUNI
9
Documents
Publications
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ChaboNet : Design of a deep CNN for prediction of visual saliency in natural videoJournal of Visual Communication and Image Representation, 2019, 60, pp.79-93. ⟨10.1016/j.jvcir.2019.02.004⟩
Article dans une revue
hal-02326279v1
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Prediction of visual attention with deep CNN on artificially degraded videos for studies of attention of patients with DementiaMultimedia Tools and Applications, 2017
Article dans une revue
hal-01674982v1
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Early and Late Fusion of Temporal Information for Classification of Surgical Actions in Laparoscopic Gynecology2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS), Jun 2018, Karlstad, France. ⟨10.1109/CBMS.2018.00071⟩
Communication dans un congrès
hal-01898488v1
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Transfer learning with deep networks for saliency prediction in natural videImage Processing (ICIP), 2016 IEEE International Conference on, Sep 2016, Phoenix, Arizona, United States. pp.1604-1608, ⟨10.1109/ICIP.2016.7532629⟩
Communication dans un congrès
hal-01436695v1
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Prediction of visual saliency in video with deep CNNsSPIE Optical Engineering+ Applications, Aug 2016, San Diego, California, United States. pp.99711Q-99711Q-14, ⟨10.1117/12.2238956⟩
Communication dans un congrès
hal-01436651v1
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Prediction of visual attention with Deep CNN for studies of neurodegenerative diseasesContent-Based Multimedia Indexing (CBMI), 2016 14th International Workshop on, Jun 2016, Bucharest, Romania. pp.1-6, ⟨10.1109/CBMI.2016.7500243⟩
Communication dans un congrès
hal-01436845v1
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Particle swarm optimization for support vector clustering Separating hyper-plane of unlabeled data5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO), Apr 2013, Hammamet, Tunisia. ⟨10.1109/ICMSAO.2013.6552696⟩
Communication dans un congrès
hal-01223462v1
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Deep saliency:prediction of interestingness in video with CNNVisual Content Indexing and Retrieval with Psycho-Visual Models, 2017
Chapitre d'ouvrage
hal-01674938v1
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Deep Learning for Saliency Prediction in Natural Video2016
Pré-publication, Document de travail
hal-01251614v1
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