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ORCIDMohamed-Cherif Rahal
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2020 – today
- 2021
[j3]Florent Chiaroni
, Mohamed-Cherif Rahal, Nicolas Hueber, Frédéric Dufaux:
Self-Supervised Learning for Autonomous Vehicles Perception: A Conciliation Between Analytical and Learning Methods. IEEE Signal Process. Mag. 38(1): 31-41 (2021)- 2020
- [j2]Florent Chiaroni, Ghazaleh Khodabandelou, Mohamed-Cherif Rahal, Nicolas Hueber, Frédéric Dufaux:
Counter-examples generation from a positive unlabeled image dataset. Pattern Recognit. 107: 107527 (2020)
2010 – 2019
- 2019
- [c10]Dominique Gruyer, Mohamed-Cherif Rahal:
Multi-Layer Laser Scanner Strategy for Obstacle Detection and Tracking. AICCSA 2019: 1-8 - [c9]Florent Chiaroni, Mohamed-Cherif Rahal, Nicolas Hueber, Frédéric Dufaux:
Hallucinating A Cleanly Labeled Augmented Dataset from A Noisy Labeled Dataset Using GAN. ICIP 2019: 3616-3620 - [i5]Florent Chiaroni, Mohamed-Cherif Rahal, Nicolas Hueber, Frédéric Dufaux:
Self-supervised learning for autonomous vehicles perception: A conciliation between analytical and learning methods. CoRR abs/1910.01636 (2019) - [i4]Florent Chiaroni, Ghazaleh Khodabandelou, Mohamed-Cherif Rahal, Nicolas Hueber, Frédéric Dufaux:
Generating Relevant Counter-Examples from a Positive Unlabeled Dataset for Image Classification. CoRR abs/1910.01968 (2019) - [i3]Sid Ali Hamideche, Florent Chiaroni, Mohamed-Cherif Rahal:
Self-supervised classification of dynamic obstacles using the temporal information provided by videos. CoRR abs/1910.09094 (2019) - 2018
- [c8]Florent Chiaroni, Mohamed-Cherif Rahal, Nicolas Hueber, Frédéric Dufaux:
Learning with A Generative Adversarial Network From a Positive Unlabeled Dataset for Image Classification. ICIP 2018: 1368-1372 - [c7]Florent Chiaroni, Mohamed-Cherif Rahal, Frédéric Dufaux, Nicolas Hueber:
Classification d'images en apprenant sur des échantillons positifs et non labélisés avec un réseau antagoniste génératif(Image classification by learning on positive and unlabeled samples with a generative adversarial network). CNIA+RJCIA 2018: 35-42 - [i2]Hatem Hajri, Emmanuel Doucet, Marc Revilloud, Lynda Halit, Benoît Lusetti, Mohamed-Cherif Rahal:
Automatic generation of ground truth for the evaluation of obstacle detection and tracking techniques. CoRR abs/1807.05722 (2018) - [i1]Hatem Hajri, Mohamed-Cherif Rahal:
Real Time Lidar and Radar High-Level Fusion for Obstacle Detection and Tracking with evaluation on a ground truth. CoRR abs/1807.11264 (2018) - 2016
- [c6]Marc Revilloud, Dominique Gruyer, Mohamed-Cherif Rahal:
A new multi-agent approach for lane detection and tracking. ICRA 2016: 3147-3153 - [c5]Marc Revilloud, Dominique Gruyer, Mohamed-Cherif Rahal:
A lane marker estimation method for improving lane detection. ITSC 2016: 289-295 - [c4]Guillaume Bresson, Mohamed-Cherif Rahal, Dominique Gruyer, Marc Revilloud, Zayed Alsayed:
A cooperative fusion architecture for robust localization: Application to autonomous driving. ITSC 2016: 859-866 - [c3]Badis Hammi, Mohamed Cherif Rahal, Rida Khatoun:
Clustering methods comparison: Application to source based detection of botclouds. SSIC 2016: 1-7 - 2010
- [j1]Mohamed Cherif Rahal:
Un nouvel algorithme de classification spatiale. Monde des Util. Anal. Données 42: 118-126 (2010)
2000 – 2009
- 2008
- [c2]Myriam Touati, Mohamed Cherif Rahal, Filipe Afonso, Edwin Diday:
Le logiciel SODAS : avancées récentes Un outil permettant d'analyser et de visualiser des données symboliques. EGC 2008: 239-240 - 2005
- [c1]Kutluhan Kemal Pak, Mohamed Cherif Rahal, Edwin Diday:
Elagage et aide à l'interprétation symbolique et graphique d'une pyramide. EGC 2005: 135-146
Coauthor Index
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