A New Hybrid Possibilistic-Probabilistic Decision-Making Scheme for Classification

Autor: Basel Solaiman, Didier Guériot, Shaban Almouahed, Bassem Alsahwa, Éloi Bossé

Publikováno v: Entropy, Vol 23, Iss 1, p 67 (2021)

Uncertainty is at the heart of decision-making processes in most real-world applications. Uncertainty can be broadly categorized into two types: aleatory and epistemic. Aleatory uncertainty describes the variability in the physical system where senso

Externí odkaz: https://doaj.org/article/9b4f10015dcb4aaebb088216dc1c03e4

The use of contextual spatial knowledge for low-quality image segmentation

Autor: Shaban Almouahed, Bassem Alsahwa, Imene Khanfir Kallel, Basel Solaiman

Publikováno v: Multimedia Tools and Applications. 78:9645-9665

In this paper, a novel possibilistic approach for representing pixelic spatial knowledge is proposed to be used in classification; more specifically in segmentation of low quality images. This approach uses the spatial contextual information at the p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::15d98a5f8666a82cf0dedff9cbdde389
https://doi.org/10.1007/s11042-018-6540-1

Iterative Refinement of Possibility Distributions by Learning for Pixel-Based Classification

Autor: Bassem Alsahwa, Basel Solaiman, Shaban Almouahed, Eloi Bosse, Didier Gueriot

Publikováno v: IEEE Transactions on Image Processing
IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2016, 25 (8), pp.3533-3545. ⟨10.1109/TIP.2016.2574992⟩

International audience; This paper proposes an approach referred as: iterative refinement of possibility distributions by learning (IRPDL) for pixel-based image classification. The IRPDL approach is based on the use of possibilistic reasoning concept

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb9436dd2569ed1ccc45a24b88c4f0f1
https://doi.org/10.1109/tip.2016.2574992

A method of pixel unmixing by classes based on the possibilistic similarity

Autor: Shaban Almouahed, Didier Gueriot, Bassem Alsahwa, Bassel Solaiman

Publikováno v: ICPRAM
Proceedings ICPRAM 2014 : the International Conference on Pattern Recognition Applications and Methods
ICPRAM 2014 : the International Conference on Pattern Recognition Applications and Methods
ICPRAM 2014 : the International Conference on Pattern Recognition Applications and Methods, Mar 2014, Angers, France. pp.220-226
HAL

International audience; In this study, an approach for pixel unmixing based on possibilistic similarity is proposed. This approach, due to the use of possibilistic concepts, enables an important flexibility to integrate both contextual information an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::92f7caba6d5943964f04138aafb1e2f4
https://hal.archives-ouvertes.fr/hal-01213691

Classification d'images basée sur l'utilisation de la similarité possibiliste

Autor: Bassem Alsahwa, Shaban Almouahed, Didier GUERIOT, Sylvie Daniel, Basel Solaiman

Publikováno v: Actes TAIMA 2011 : traitement et analyse de l'information méthodes et applications
TAIMA 2011 : traitement et analyse de l'information méthodes et applications
TAIMA 2011 : traitement et analyse de l'information méthodes et applications, Oct 2011, Hammamet, Tunisie
HAL

International audience; Dans cette étude, un modèle de classification d'images basée sur la similarité possibiliste est proposé. Ce modèle, en raison de l'utilisation de concepts possibilistes, présente la flexibilité d'intégrer à la fois d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::b851ee942d58300f201730a7f4eade0d
https://hal.archives-ouvertes.fr/hal-01213689