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Yannick Bourrier

Researcher at University of Savoy

Publications -  14
Citations -  59

Yannick Bourrier is an academic researcher from University of Savoy. The author has contributed to research in topics: Artificial neural network & Situated learning. The author has an hindex of 3, co-authored 12 publications receiving 41 citations. Previous affiliations of Yannick Bourrier include University of Paris & Grenoble Institute of Technology.

Papers
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Journal ArticleDOI

Simulation and virtual reality-based learning of non-technical skills in driving: critical situations, diagnostic and adaptation

TL;DR: The paper describes and justifies the main concepts, the approach and the architecture elaborated from a multidisciplinary viewpoint in order to provide more appropriate and flexible Virtual Environments for Learning/Training to support the acquisition.
Proceedings ArticleDOI

Impact of Spatial Frequency Based Constraints on Adversarial Robustness

TL;DR: In this article, the authors investigate the robustness to adversarial perturbations of models enforced during training to leverage information corresponding to different spatial frequency ranges and show that it is tightly linked to the spatial frequency characteristics of the data at stake.
Dissertation

Diagnostic et prise de décision pédagogique pour la construction de compétences non-techniques en situation critique

TL;DR: In this paper, the authors propose an architecture for diagnostic of competences non-techniques (CNTs), i.e., a panel of capacites metacognitives complementing the competences techniques, and garantissant the realisation of a technique sure.
Book ChapterDOI

An Approach to the TEL Teaching of Non-technical Skills from the Perspective of an Ill-Defined Problem

TL;DR: It is shown that some aspects of this problem have not been encompassed yet in the ill-defined domains literature, and should be further studied in any attempt at teaching behaviours inducing technical and non-technical skills in a virtual world.
Journal ArticleDOI

The importance of recurrent top-down synaptic connections for the anticipation of dynamic emotions.

TL;DR: Results suggest that, despite the cost of recurrent connections in terms of energy and processing time for biological organisms, they can provide a substantial advantage for the fast recognition of uncertain visual signals.