Sabra Mabrouk

Sabra Mabrouk
Ecole Nationale des Sciences de l'Informatique

About

19
Publications
2,764
Reads
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71
Citations
Citations since 2017
12 Research Items
64 Citations
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Introduction
Skills and Expertise

Publications

Publications (19)
Conference Paper
Full-text available
La rétinopathie diabétique (RD), est l'une des principales causes de cécité chez l'adulte. C'est une affection oculaire qui affecte 80 %à 85 % des patients atteints de diabète depuis plus de dix ans. Le diagnostic assisté par ordinateur facilite le traitement précis et en temps opportun, et les images du fundus rétinien sont couramment utilisées po...
Chapter
In recent years, cities are experiencing a deep negative impact due to traffic congestion. As the number of vehicles is increasing rapidly, traffic congestion becomes unsustainable in urban domains specially in peak hours leading to time and fuel waste, accidents, additional costs for the economy, environmental problems and consequently impaired qu...
Chapter
Due to the huge number of accidents, improving driving safety around the world is becoming a priority. Providing efficient and cost effective solutions to detect driving behavior is quite a challenging research topic worldwide. Exploring several technologies including big data, machine learning, data mining and data analysis in general can help res...
Article
Due to the increasing number of vehicles in circulation in different urban cities, several automatic traffic monitoring systems have been developed. In particular, traffic monitoring systems using roadside cameras are becoming extensively deployed, as they offer imperative technological advantages compared with other traffic monitoring systems. Veh...
Conference Paper
Full-text available
In this paper we intend to introduce a new representativeness criterion of the Bootstrap sample for images segmentation. Using the plug-in method in order to estimate probability density functions (pdf), we present a robust and stable criterion based on L 2 distance between the estimated probability density from the bootstrap sample and the empiric...
Chapter
Vehicle detection plays a significant role in traffic monitoring. Vehicle detection approaches can be used for vehicle tracking, vehicle classification and traffic analysis. However, numerous attributes like shape, intensity, size, pose, illumination, shadows, occlusion, velocity of vehicles and environmental conditions, provide different challenge...
Chapter
Full-text available
In the context of platooning, a high degree of cooperation between platooning members is required to perform major maneuvers. One of the most challenging issues is to perform join-maneuver due to the strong interference caused by unintended vehicles entering in the middle during this maneuver. In order to detect and identify vehicles (unintended or...
Chapter
In recent years, cities are experiencing a deep negative impact due to traffic congestion. As the number of vehicles is increasing rapidly, traffic congestion becomes unsustainable in urban domains specially in peak hours leading to time and fuel waste, accidents, additional costs for the economy, environmental problems and consequently impaired qu...
Conference Paper
In this paper we propose a new multi-scale fully automatic algorithm based on Graph cuts for vessel extraction. In fact, we combine vesselness, geodesic paths, a multi-scale edgeness map and the directional information for vessel tracking in order to personalize the Graph cuts approach to the segmentation of tubular structures.
Article
Full-text available
Context X-ray angiography is the most used tool by clinician to diagnose the majority of cardiovascular disease and deformations in coronary arteries like stenosis. In most applications involving angiograms interpretation, accurate segmentation is essential to extract the coronary artery tree and thus speed up the medical intervention. Materials a...
Article
Full-text available
Segmentation and volume measurement of liver tumor are important tasks for surgical planning and cancer follow-up. In this work, a segmentation method from four-phase computed tomography images is proposed. It is based on the combination of the Expectation-Maximization algorithm and the Hidden Markov Random Fields. The latter considers the spatial...
Conference Paper
Full-text available
We propose a new 3D mesh segmentation method based on the HMRF-EM framework. The clustering method relies on the curvature attribute and considers the spatial information encoded by the mutual influences of neighboring mesh elements. A region growing process is then carried out in order to extract connected regions followed by a merging procedure....
Conference Paper
Full-text available
Accurate liver tumors detection and segmentation is a crucial task for many clinical applications such as surgical planning and cancer following-up. In order to improve the segmentation process, denoising techniques are required. They remove the locally varying and oriented noise in computed tomography (CT) images. In this work, we propose to use t...
Conference Paper
In this paper we intend to introduce a new representativeness criterion of the Bootstrap sample for images segmentation. Using the plug-in method in order to estimate probability density functions (pdf), we present a robust and stable criterion based on L2 distance between the estimated probability density from the bootstrap sample and the empirica...
Conference Paper
Full-text available
In this paper we intend to introduce a new representativeness criterion of the Bootstrap sample for images segmentation. Using the plug-in method in order to estimate probability density functions (pdf), we present a robust and stable criterion based on L 2 distance between the estimated probability density from the bootstrap sample and the empiric...
Article
Full-text available
We are interested in this work to optimize the algorithmic complexity of Markovian segmentation of brain tissues in MRI by the Bootstrap sampling. The introduction of this resampling allows to create the independence conditions which gives a better convergence of the mixture identification algorithm. A comparative study is made with the non-bootstr...
Article
Full-text available
Ce papier s’inscrit dans le cadre des méthodes de segmentation stochastique des images à résonance magnétique (IRM) cérébrale qui se basent conjointement sur la modélisation markovienne et la famille d’algorithmes d’identification de mélange de type Estimation-Maximisation (EM) (Hidden Markov Random Field [HMRF-EM]) et faisant appel à l’échantillon...
Article
Here, we intend to introduce new face invariant descriptors, composed by two kinds of features, in order to explore the problem of faces classification. The first kind is defined from the p-order moments of a curvature function of the geodesic curve according to its arc length. The second one describes relative positions between important localitie...

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