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CVPR
2012
IEEE
13 years 4 months ago
Background segmentation with feedback: The Pixel-Based Adaptive Segmenter
In this paper we present a novel method for foreground segmentation. Our proposed approach follows a nonparametric background modeling paradigm, thus the background is modeled by ...
Martin Hofmann 0011, Philipp Tiefenbacher, Gerhard...
HIS
2008
15 years 3 months ago
Neural Plasticity and Minimal Topologies for Reward-Based Learning
Artificial Neural Networks for online learning problems are often implemented with synaptic plasticity to achieve adaptive behaviour. A common problem is that the overall learning...
Andrea Soltoggio
ESANN
2003
15 years 3 months ago
Autonomous learning algorithm for fully connected recurrent networks
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
Edouard Leclercq, Fabrice Druaux, Dimitri Lefebvre
MMAS
2011
Springer
14 years 9 months ago
Scalable Bayesian Reduced-Order Models for Simulating High-Dimensional Multiscale Dynamical Systems
While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and thei...
Phaedon-Stelios Koutsourelakis, Elias Bilionis
CVPR
2000
IEEE
16 years 4 months ago
Impact of Dynamic Model Learning on Classification of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and analysis of figure motion has employed eith...
Vladimir Pavlovic, James M. Rehg