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Souad Chaabouni
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2010 – 2019
- 2019
- [j2]Souad Chaabouni, Jenny Benois-Pineau
, Chokri Ben Amar:
ChaboNet : Design of a deep CNN for prediction of visual saliency in natural video. J. Vis. Commun. Image Represent. 60: 79-93 (2019) - [c4]Souad Chaabouni, Frédéric Precioso:
Impact of Saliency and Gaze Features on Visual Control: Gaze-Saliency Interest Estimator. ACM Multimedia 2019: 1367-1374 - 2018
- [c3]Stefan Petscharnig, Klaus Schöffmann, Jenny Benois-Pineau
, Souad Chaabouni, Jörg Keckstein:
Early and Late Fusion of Temporal Information for Classification of Surgical Actions in Laparoscopic Gynecology. CBMS 2018: 369-374 - 2017
- [b1]Souad Chaabouni:
Etude et prédiction d'attention visuelle avec les outils d'apprentissage profond en vue d'évaluation des patients atteints des maladies neuro-dégénératives. (Study and prediction of visual attention with deep learning networks in view of assessment of patients with neurodegenerative diseases). University of Bordeaux, France, 2017 - [j1]Souad Chaabouni, Jenny Benois-Pineau
, Francois Tison, Chokri Ben Amar, Akka Zemmari
:
Prediction of visual attention with deep CNN on artificially degraded videos for studies of attention of patients with Dementia. Multim. Tools Appl. 76(21): 22527-22546 (2017) - [p1]Souad Chaabouni, Jenny Benois-Pineau, Akka Zemmari
, Chokri Ben Amar:
Deep Saliency: Prediction of Interestingness in Video with CNN. Visual Content Indexing and Retrieval with Psycho-Visual Models 2017: 43-74 - 2016
- [c2]Souad Chaabouni, Francois Tison, Jenny Benois-Pineau
, Chokri Ben Amar:
Prediction of visual attention with Deep CNN for studies of neurodegenerative diseases. CBMI 2016: 1-6 - [c1]Souad Chaabouni, Jenny Benois-Pineau
, Chokri Ben Amar:
Transfer learning with deep networks for saliency prediction in natural video. ICIP 2016: 1604-1608 - [i1]Souad Chaabouni, Jenny Benois-Pineau, Ofer Hadar, Chokri Ben Amar:
Deep Learning for Saliency Prediction in Natural Video. CoRR abs/1604.08010 (2016)
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