Profil

Seddati Omar

Université de Mons - UMONS > Faculté Polytechnique > Service Information, Signal et Intelligence artificielle

Université de Mons - UMONS > Recherche > Service de l'Institut Numédiart pour les Technologies créatives

Université de Mons - UMONS > Faculté Polytechnique > Information, Signal et Intelligence artificielle

ORCID
0000-0002-0573-8480
Principaux co-auteurs référencés
DUPONT, Stéphane  (27)
MAHMOUDI, Saïd  (16)
Rossetto, Luca (9)
Schuldt, Heiko (9)
Giangreco, Ivan (7)
Principaux mots-clés référencés
Sketch-based image retrieval (2); accessibility (1); assistive technology (1); Batch sizes (1); blind (1);
Principaux centres et unités de recherche référencés
CRTI - Centre de Recherche en Technologie de l'Information (23)
Principales disciplines référencées
Bibliothéconomie & sciences de l’information (21)
Sciences informatiques (8)

La plus téléchargée
66 téléchargements
Stragier, V., Dutoit, T., Seddati, O., & Vandenbulcke, V. (2023). Developing an Interactive Agent for Blind and Visually Impaired People. In IMX '23: ACM International Conference on Interactive Media Experiences. New York, United States - New York: Association for Computing Machinery. doi:10.1145/3573381.3596471 https://hdl.handle.net/20.500.12907/46215

La plus citée

39 citations (Scopus®)

Seddati, O., Dupont, S., Mahmoudi, S., & Amiri Parian, M. (2017). Towards Good Practices for Image Retrieval Based on CNN Features [Paper presentation]. IEEE International Conference on Computer Vision, Venice, Italy. https://hdl.handle.net/20.500.12907/42060

Stragier, V., Dutoit, T., Seddati, O., & Vandenbulcke, V. (2023). Developing an Interactive Agent for Blind and Visually Impaired People. In IMX '23: ACM International Conference on Interactive Media Experiences. New York, United States - New York: Association for Computing Machinery. doi:10.1145/3573381.3596471
Peer reviewed

Seddati, O., Hubens, N., Dupont, S., & Dutoit, T. (2023). A Recipe for Efficient SBIR Models: Combining Relative Triplet Loss with Batch Normalization and Knowledge Distillation. ORBi UMONS-University of Mons. https://orbi.umons.ac.be/handle/20.500.12907/48304.

Seddati, O., Dupont, S., Mahmoudi, S., & Dutoit, T. (2022). Towards Human Performance on Sketch-Based Image Retrieval. In Proceedings of 19th International Conference on Content-based Multimedia Indexing, CBMI 2022. Association for Computing Machinery. doi:10.1145/3549555.3549582
Peer reviewed

Seddati, O., Dupont, S., Mahmoudi, S., & Dutoit, T. (2022). Transformers and CNNs both Beat Humans on SBIR. ORBi UMONS-University of Mons. https://orbi.umons.ac.be/handle/20.500.12907/43859. doi:10.48550/arXiv.2209.06629

Seddati, O. (2018). Reconnaissance et Recherche de Données Multimédia par les Réseaux de Neurones Profonds [Doctoral thesis, Université de Mons]. ORBi UMONS-University of Mons. https://orbi.umons.ac.be/handle/20.500.12907/42315

Seddati, O., Dupont, S., Mahmoudi, S., & Amiri Parian, M. (2017). Towards Good Practices for Image Retrieval Based on CNN Features [Paper presentation]. IEEE International Conference on Computer Vision, Venice, Italy.

Seddati, O., Ben-Lhachemi, N., Dupont, S., & Mahmoudi, S. (2017). UMONS @ MediaEval 2017: Diverse Social Images Retrieval [Paper presentation]. MediaEval Benchmarking Initiative for Multimedia Evaluation, Dublin, Ireland.

Delbrouck, J.-B., Dupont, S., & Seddati, O. (2017). Visually Grounded Word Embeddings and Richer Visual Features for Improving Multimodal Neural Machine Translation [Paper presentation]. GLU 2017 International Workshop on Grounding Language Understanding, Stockholm, Sweden.

Seddati, O., Dupont, S., & Mahmoudi, S. (2017). Triplet Networks Feature Masking for Sketch-Based Image Retrieval. Lecture Notes in Computer Science.
Peer reviewed

Seddati, O., Dupont, S., & Mahmoudi, S. (2017). Quadruplet Networks for Sketch-Based Image Retrieval. ACM on International Conference on Multimedia Retrieval.
Peer reviewed

Seddati, O., Dupont, S., & Mahmoudi, S. (2017). DeepSketch 3: Analyzing deep neural networks features for better sketch recognition and sketch-based image retrieval. Multimedia Tools and Applications, 1-27. doi:10.1007/s11042-017-4799-2, 2017
Peer reviewed vérifié par ORBi

Seddati, O., Delbrouck, J.-B., Dupont, S., & Mahmoudi, S. (25 April 2017). Deep Features for Big Data [Poster presentation]. Journée scientifique du Pôle hainuyer 'Les données au coeur de notre devenir: les enjeux des big data, Tournai, e-campus, Belgium.

Rossetto, L., Giangreco, I., Tanase, C., Schuldt, H., Dupont, S., & Seddati, O. (2017). Enhanced Retrieval and Browsing in the IMOTION System [Paper presentation]. Conference on Multimedia Modeling, Reykjavik, Iceland.

Seddati, O., Dupont, S., & Mahmoudi, S. (2016). DeepSketch2Image: Deep Convolutional Neural Networks for Partial Sketch Recognition and Image Retrieval. ACM on Multimedia Conference, Amsterdam, The Netherlands, 2016, 739-741.
Peer reviewed

Tanase, C., Rossetto, L., Giangreco, I., Schuldt, H., Dupont, S., & Seddati, O. (2016). The IMOTION System at TRECVID 2016: The Ad-Hoc Video Search Task [Paper presentation]. TREC Video Retrieval Evaluation, .

Seddati, O., Dupont, S., & Mahmoudi, S. (2016). DeepSketch 2: Deep Convolutional Neural Networks for Partial Sketch Recognition. International Workshop on Content-based Multimedia Indexing, CBMI 2016, Bucharest, Romania, June 15-17, 2016.
Peer reviewed

Seddati, O., Dupont, S., & Mahmoudi, S. (2016). Réseaux de Neurones Convolutionnels Profonds pour la Reconnaissance d'Action dans les Vidéos [Paper presentation]. CORESA 2016 - COmpression et REprésentation des Signaux Audiovisuels, Nancy, France.

Tanase, C., Giangreco, I., Rossetto, L., Schuldt, H., Seddati, O., Dupont, S., Altiok, O. C., & Sezgin, M. (2016). Semantic Sketch-Based Video Retrieval with Autocompletion [Paper presentation]. International Conference on Intelligent User Interfaces, Sonoma, United States - California.

Schuldt, H., Dupont, S., Giangreco, I., Rossetto, L., Sahillioglu, Y., Seddati, O., Sen, C., Sezgin, M., Tanase, C., & Yildirim, D. (2016). IMOTION - Intelligent MultiModal Augmented Video Motion Retrieval System - Periodic Report 2.

Seddati, O., Dupont, S., & Mahmoudi, S. (2016). Video Motion Feature Extractors, 1st Prototype - IMOTION Deliverable 2.2.

Rossetto, L., Giangreco, I., Heller, S., Tanase, C., Schuldt, H., Dupont, S., Seddati, O., Sezgin, M., Altiok, O. C., & Sahillioglu, Y. (2016). IMOTION - Searching for Video Sequences Using Multi-Shot Sketch Queries. Lecture Notes in Computer Science.
Peer reviewed

Rossetto, L., Giangreco, I., Tanase, C., Schuldt, H., Dupont, S., Seddati, O., Sezgin, M., & Sahillioglu, Y. (2016). iAutoMotion - an Autonomous Content-Based Video Retrieval Engine. Lecture Notes in Computer Science.
Peer reviewed

Seddati, O., Emre, K., Pironkov, G., Dupont, S., Mahmoudi, S., & Dutoit, T. (2015). UMons at MediaEval 2015 Affective Impact of Movies Task including Violent Scenes Detection. IEEE Multimedia.
Peer reviewed vérifié par ORBi

Seddati, O., Dupont, S., & Mahmoudi, S. (2015). DeepSketch: Deep convolutional neural networks for sketch recognition and similarity search. International Workshop on Content-Based Multimedia Indexing, CBMI 2015, Prague, Czech Republic, June 10-12, 2015.
Peer reviewed

Seddati, O., Dupont, S., & Mahmoudi, S. (10 March 2015). DNN for action recognition in videos [Poster presentation]. 8ème édition de la Matinée de Chercheurs, Mons, Belgium.

Seddati, O., Dupont, S., & Mahmoudi, S. (2015). Report on Video Motion Feature Extraction - IMOTION Deliverable 2.1.

Schuldt, H., Dupont, S., Giangreco, G., Rossetto, L., Sahillioglu, Y., Seddati, O., Sen, C., Sezgin, M., Tanase, C., & Yildirim, D. (2015). IMOTION - Intelligent MultiModal Augmented Video Motion Retrieval System - Periodic Report 1.

Rossetto, L., Giangreco, I., Schuldt, H., Dupont, S., Seddati, O., Sezgin, M., & Sahillioglu, Y. (01 January 2015). IMOTION - A Content-Based Video Retrieval Engine. Lecture Notes in Computer Science, 8936, 255-260.
Peer reviewed

Giangreco, G., Rossetto, L., Schuldt, H., Sezgin, M., Sahillioglu, Y., Dupont, S., & Seddati, O. (2014). Initial Requirements and System Specification - IMOTION Deliverable 1.1.

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