The I3S LABORATORY

It's on the SophiaTech campus in the heart of the Sophia Antipolis technology park our laboratory conducts research in the field of information science and communication.
"Advancing knowledge, consider the economic and technological realities, while imagining tomorrow's solutions."

The I3S laboratory is one of the largest information and communication science laboratories in the French Riviera. it was one of first ones to settle down on Sophia Antipolis Science and Technology Park. It consists of a little less than 300 people. [+...]

In partnership with CNRS and INRIA, and numerous industrial collaborations, we work on the themes of innovative research at the cutting edge of science and technology: systems and networks ubiquitous, biology and digital health, modeling for environment interactions and practices. [+...]

 

 

 

 

The laboratory is organized in 4 teams:

COMRED team (French acronym for Communications, Networks, Embedded Systems, Distributed Systems)
MDSC team (French acronym for Discrete Models for Complex System)
SIS team (Signal, Image and Systems)
SPARKS team (Scalable and Pervasive softwARe and Knowledge Systems)

The 5 latest submissions recorded in HAL

Mansour Zoubeirou a Mayaki, Michel Riveill.
AnoRand: A Semi Supervised Deep Learning Anomaly Detection Method by Random Labeling.
2023
Aurelie Calabrese, Alexandre Bonlarron, Jean-Charles Régin, Pierre Kornprobst.
A new method to generate automatically highly standardized reading chart text in multiple languages: the case of MNREAD.
ARVO 2024, May 2024, Seattle (USA), Washington, United States
Pierre Maillot, Jennie Andersen, Sylvie Cazalens, Catherine Faron, Fabien Gandon, Philippe Lamarre, Franck Michel.
An Open Platform for Quality Measures in a Linked Data Index.
WWW '24: The ACM Web Conference 2024, May 2024, Singapore Singapore, France. pp.1087-1090, ⟨10.1145/3589335.3651443⟩
Julien Bensmail, Clara Marcille.
Strongly Locally Irregular Graphs and Decompositions.
2024
Ezio Malis.
A Novel Closed-Form Approach for Enhancing Efficiency in Pose Estimation from 3D Correspondences.
IEEE Robotics and Automation Letters, 2024, ⟨10.1109/LRA.2024.3349954⟩