Filtrage EPSF pour l'amélioration d'image

Disponible dans les fichiers attachés à ce documen

Filtrage adaptatif par diffusion anisotropique multiechelle base sur le principe du maximum d'entropie

Projet SYNTIMRésumé disponible dans le fichier PD

A Local Active Learning Strategy by Cooperative Multi-Agent Systems

International audienceIn this paper, we place ourselves in the context learning approach and we aim to show that adaptive multiagent systems are a relevant solution to its enhancement with local active learning strategy. We use a local learning approach inspired by constructivism: context learning by adaptive multi-agent systems. We seek to introduce active learning requests as a mean of internally improving the learning process by detecting and resolving imprecisions between the learnt knowledge. We propose a strategy of local active learning for resolving learning inaccuracies. In this article, we evaluate the performance of local active learning. We show that the addition of active learning requests facilitated by self-observation accelerates and generalizes learning, intelligently selects learning data, and increases performance on prediction errors

Cooperative Neighborhood Learning: Application to Robotic Inverse Model

International audienceIn this paper we present a generic multiagent learning system based on context learning applied in robotics. By applying learning with multiagent systems in robotics, we propose an endogenous self-learning strategy to improve learning performances. Inspired by constructivism, this learning mechanism encapsulates models in agents. To enhance the learning performance despite the weak amount of data, local and internal negotiation, also called cooperation, is introduced. Agents collaborate by generating artificial learning situations to improve their model. A second contribution is a new exploitation of the learnt models that allows less training. We consider highly redundant robotic arms to learn their Inverse Kinematic Model. A multiagent system learns a collective of models for a robotic arm. The exploitation of the models allows to control the end position of the robotic arm in a 2D/3D space. We show how the addition of artificial learning situations increases the performances of the learnt model and decreases the required labeled learning data. Experimentations are conducted on simulated arms with up to 30 joints in a 2D task space

Contourite identification along Italian margins: The case of the Portofino drift (Ligurian Sea)

A brief review of the published evidence of current deposits around Italy is the occasion to test the robustness of matching bottom current velocity models and seafloor morphologies to identify contourite drifts not yet documented. We present the result of the regional hydrodynamic model MARS3D in the Northern Tyrrhenian and Ligurian Sea with horizontal resolution of 1.2 km and 60 levels with focus on bottom current: data are integrated over summer and winter 2013 as representative of low and high intensity current conditions. The Eastern Ligurian margin is impacted by the Levantine Intermediate Water (LIW) with modeled mean velocity of bottom current up to 20 cm s−1 in winter 2013 and calculated bottom shear stress exceeding 0.2 N m−2 in water depth of 400–800 m. By crossing this information with seafloor morphology and geometry of seismic reflections, we identify a sediment drift formerly overlooked at ca 1000 m water depth. The Portofino separated mounded drift has a maximum thickness of at least 150 m and occurs in an area of mean current velocity minimum. Independent evidence to support the interpretation include bottom current modelling, seafloor morphology, seismic reflection geometry and sediment core facies. The adjacent areas impacted by stronger bottom currents present features likely resulted from bottom current erosion such as a marine terrace and elongated pockmarks. Compared to former interpretation of seafloor morphology in the study area, our results have an impact on the assessment of marine geohazards: submarine landslides offshore Portofino are small in size and coexist with sediment erosion and preferential accumulation features (sediment drifts) originated by current-dominated sedimentary processes. Furthermore, our results propel a more general discussion about contourite identification in the Italian seas and possible implications

Filtrage adaptatif par diffusion anisotropique multiechelle base sur le principe du maximum d'entropie

Programme 4 : robotique, image et visionAvailable at INIST (FR), Document Supply Service, under shelf-number : 14802 E, issue : a.1994 n.2174 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueSIGLEFRFranc

Filtrage EPSF pour l'amelioration d'image

Programme 4 : robotique, image et visionAvailable at INIST (FR), Document Supply Service, under shelf-number : 14802 E, issue : a.1994 n.2175 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueSIGLEFRFranc