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Loïc Fricoteaux

dblp:27/10370 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorHuman-computer interaction and ubiquitous computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Learning and educational technologies · 100%
Computer graphics and multimedia
1 paper
Virtual and augmented reality · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Virtual and augmented reality › virtual environment
immersive virtual environments
0.012013
OSE: An adaptive user interface for fluvial navigation training · VR 2013
Virtual and augmented reality › virtual environment
virtual training environments
0.012013
OSE: An adaptive user interface for fluvial navigation training · VR 2013

Methods — techniques the papers use, named apart from their topics

visualization metaphors · 0.3decision making module · 0.3
YearPublicationVenuePosition
2014 GULLIVER: A decision-making system based on user observation for an adaptive training in informed virtual environments
Loïc Fricoteaux, Indira Thouvenin, Daniel Mestre
Eng. Appl. Artif. Intell.1
2013 OSE: An adaptive user interface for fluvial navigation training
abstract
As training systems are often designed for procedural task learning, we propose an adaptive training system (OSE) in this context to explore how informed interaction supported by a decision making module (GULLIVER) contributes to adaptive knowledge acquisition in a virtual environment. Visualization metaphors and audio messages are displayed as feedback to guide the learner, which is essential to this training. First results show that our system provides an adaptive guiding which is efficient for beginners. Though we focus on fluvial navigation training, the results may be relevant to other applications.
Loïc Fricoteaux, Indira Thouvenin
VR1