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Institution

Orange S.A.

CompanyParis, France
About: Orange S.A. is a company organization based out in Paris, France. It is known for research contribution in the topics: Terminal (electronics) & Signal. The organization has 6735 authors who have published 9190 publications receiving 156440 citations. The organization is also known as: Orange SA & France Télécom.


Papers
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Proceedings ArticleDOI
11 Dec 2006
TL;DR: New architectural concepts regarding the implementation of a service capability interaction manager as well as the functionalities that this new entity must provide to avoid conflicts between service capability interactions in order to implement integrated services based on the standardized service capabilities are defined.
Abstract: Reusing service capabilities to implement different integrated services in Next Generation networks (NGN) provides flexible and open service architecture capable of creating innovative services that do not need to be standardized and are based on the standardized service capabilities. In this architecture, invoking each integrated service may provoke the invocation of multiple service capabilities. The service architecture must therefore provide a mechanism to manage the interactions and the incompatibilities that may occur between these service capability invocations. Due to the shortcomings in the NGN service architecture domain for defining such mechanisms, we define in this paper, new architectural concepts regarding the implementation of a service capability interaction manager as well as the functionalities that this new entity must provide to avoid conflicts between service capability interactions in order to implement integrated services based on the standardized service capabilities.

37 citations

Proceedings ArticleDOI
24 Oct 2005
TL;DR: This work presents a technique for robustly and automatically detect a set of user-selected facial features in images, like the eye pupils, the tip of the nose, the mouth centre, etc, based on a specific architecture of heterogeneous neural layers.
Abstract: We present a technique for robustly and automatically detect a set of user-selected facial features in images, like the eye pupils, the tip of the nose, the mouth centre, etc. Based on a specific architecture of heterogeneous neural layers, the proposed system automatically synthesises simple problem-specific feature extractors and classifiers from a training set of faces with annotated facial features. After training, the facial feature detection system acts like a pipeline of simple filters that treats the raw input face image as a whole and builds global facial feature maps, where facial feature positions can easily be retrieved by a simple search for global maxima. We experimentally show that our method is very robust to lighting and pose variations as well as noise and partial occlusions.

37 citations

Proceedings ArticleDOI
05 Oct 1999
TL;DR: A mesh approximation method that uses a volume-based metric that naturally and accurately fits the geometric singularities on 3D meshes and permits geometric compression leading to multiresolution meshes with minimal visual losses is introduced.
Abstract: We introduce a mesh approximation method that uses a volume-based metric. After a geometric simplification, we minimize the volume between the simplified mesh and the original mesh using a gradient-based optimization algorithm and a finite-element interpolation model implicitly defined on meshes. The notable contribution of this paper is the theoretical framework which permits the construction of a volume minimization process between two triangular meshes. We chose this volume-based metric because of its good perceptual properties, as it naturally and accurately fits the geometric singularities on 3D meshes. Furthermore, this metric corresponds well to a sort of intuitive error between two 3D surfaces and the resulting optimization algorithm only requires a few parameters. We show that this approach permits geometric compression leading to multiresolution meshes with minimal visual losses.

37 citations

Book ChapterDOI
10 Apr 2000
TL;DR: This paper details the attack on RC6 and shows how to distinguish RC6 from a random permutation and to recover the secret extended key for a fair number of rounds.
Abstract: This paper details the attack on RC6 which was announced in a report published in the proceedings of the second AES candidate conference (March 1999). Based on an observation on the RC6 statistics, we show how to distinguish RC6 from a random permutation and to recover the secret extended key for a fair number of rounds.

37 citations

Proceedings ArticleDOI
07 May 2006
TL;DR: In this article, a 10Gbit/s monolithically integrated amplified reflective electroabsorption modulator (R-EAM-SOA) is demonstrated over 50nm spectral range and over 20°C-60°C, with excellent eye diagrams.
Abstract: For high speed remote colorless modulation in FTTH technology, a new 10Gbit/s monolithically integrated amplified reflective electroabsorption modulator (R-EAM-SOA) is demonstrated over 50nm spectral range and over 20°C-60°C, with excellent eye diagrams.

37 citations


Authors

Showing all 6762 results

NameH-indexPapersCitations
Patrick O. Brown183755200985
Martin Vetterli10576157825
Samy Bengio9539056904
Aristide Lemaître7571222029
Ifor D. W. Samuel7460523151
Mischa Dohler6835519614
Isabelle Sagnes6775318178
Jean-Jacques Quisquater6533518234
David Pointcheval6429819538
Emmanuel Dupoux6326714315
David Gesbert6345624569
Yonghui Li6269715441
Sergei K. Turitsyn6172214063
Joseph Zyss6143417888
Jean-Michel Gérard5842114896
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20238
20225
20215
20205
201915
201814