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Documents
Workshop
Special Session on
Artificial Neural Networks and Intelligent Information Processing
 - ANNIIP 2012

30 - 31 July, 2012 - Rome, Italy

Within the 9th International Conference on Informatics in Control, Automation and Robotics - ICINCO 2012


CHAIR

Kurosh Madani
University of Paris-EST Créteil (UPEC)
France

 
Brief Bio
Kurosh Madani is graduated in fundamental physics in June 1985 from PARIS 7 – Jussieu University. He received his MSc. in Microelectronics and chip architecture from University PARIS 11 (PARIS-SUD), Orsay, France, in September 1986. Received his Ph.D. in Electrical Engineering and Computer Sciences from University PARIS 11 (PARIS-SUD), Orsay, France, in February 1990. In 1995, he received the DHDR Doctor Hab. degree (senior research doctorate degree) from University PARIS 12 – Val de Marne. He works as Chair Professor in Electrical Engineering of Senart-FB Institute of Technology of University PARIS-EST Creteil (UPEC), France. From 1992 to 2000 he has been creator and head of DRN (Neural Networks Division) research group. From 2001 to 2004 he has been head of Intelligence in Instrumentation and Systems Laboratory (I2S / JE 2353) of UPEC. Co-creator of Images, Signals and Intelligent Systems Laboratory (LISSI / EA 3956) of UPEC in 2005, head of Intelligent Machines & Systems” research team of LISSI, he is also Vice-director of this laboratory. He has worked on both digital and analog implementation of massively parallel processors arrays for image processing, electro-optical random number generation, and both analog and digital Artificial Neural Networks (ANN) implementation. His current research interests include: - Complex structures and behaviors modeling, - self-organizing, modular and hybrid neural based information processing systems and their real-world and industrial applications, - humanoid and collective robotics - intelligent fault detection and diagnosis systems.

SCOPE

Theoretical, applicative and technological challenges, emanating from nowadays' industrial, socioeconomic or environment needs, open every day new dilemmas to solved and new challenges to defeat. Bio-inspired Artificial Intelligence and related topic have shown its astounding potential in overcoming the above-mentioned needs. It is a fact and at the same time a great pleasure to notice that the ever-increasing interest of both confirmed and young researchers on this relatively juvenile science, upholds a reach multidisciplinary synergy between a large number of scientific communities making conceivable a forthcoming emergence of viable solutions to these real-world complex challenges.
ANNIIP takes part in appealing intellectual dynamics created around bio-inspired Artificial Intelligence by offering a privileged space to refit and exchange the knowledge about state of the art and further theoretical advances, new experimental discoveries and novel technological improvements in this promising area. The goal is to bring together different representative actors (from academia, industry, government agencies, etc...) to exchange ideas, to debate divergences and to construct convergences around these propitious concepts.

Topics of Interest
Topics of interest include, but are not limited to:

  • Bio-inspired Artificial Neural Networks
  • Hybrid Information Processing
  • Hierarchical Artificial Neural Network Models and Systems
  • Intelligent Sensors and Smart Instrumentation
  • Self-organizing Systems
  • Self-diagnosable Machines
  • Self-optimizing Systems
  • Artificial Neural Networks based Cooperative Systems
  • Social Behaviour based Systems
  • Multi-agent and Distributed Intelligent Systems
  • Neuro-Fuzzy and Fuzzy Logic based Systems
  • Complex Intelligent Artificial Systems
  • Artificial Neural Networks' Software and Hardware Issues
  • Artificial Intelligent Systems' Software and Hardware Issues
  • Modular Artificial Neural Network based Systems
  • Modular Implementation of Artificial Neural Networks
  • Stability and Instability in Artificial Neural Networks
  • Cooperative Robots and Applications
  • Humanoid Robots
  • Application of Artificial Neural Networks and Intelligent Systems:
    • Artificial Neural Networks based Pattern Recognition
    • Artificial Neural Networks based Signal Processing
    • Artificial Neural Networks based Image Processing
    • Artificial Neural Networks based Data Fusion
    • Artificial Neural Networks based Data Mining
    • Artificial Neural Networks based Decision
    • Artificial Neural Network based Control
    • Artificial Neural Network based System Identification
    • Artificial Neural Network in Robustness and Safety
    • Artificial Neural Network in Management and Financial Applications
    • Artificial Neural Network based Solutions for Industrial Environment

PROGRAM COMMITTEE MEMBERS

Veronique Amarger, University PARIS-EST Creteil (UPEC), France
Amine Chohra, Paris-East University (UPEC), France
Khalifa Djemal, University of Evry Val d'Essonne, France
Jean-Jacques Mariage, Université Paris 8, France
Dominik M. Ramík, , France
Christophe Sabourin, Univ. Paris Est Creteil, LISSI, France

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