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» Training Methods for Adaptive Boosting of Neural Networks
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ANNPR
2008
Springer
14 years 11 months ago
Combining Methods for Dynamic Multiple Classifier Systems
Most of what we know about multiple classifier systems is based on empirical findings, rather than theoretical results. Although there exist some theoretical results for simple and...
Amber Tomas
PG
2003
IEEE
15 years 3 months ago
Neural Meshes: Statistical Learning Based on Normals
We present a method for the adaptive reconstruction of a surface directly from an unorganized point cloud. The algorithm is based on an incrementally expanding Neural Network and ...
Won-Ki Jeong, Ioannis P. Ivrissimtzis, Hans-Peter ...
BMCBI
2010
152views more  BMCBI 2010»
14 years 9 months ago
Comparative study of three commonly used continuous deterministic methods for modeling gene regulation networks
Background: A gene-regulatory network (GRN) refers to DNA segments that interact through their RNA and protein products and thereby govern the rates at which genes are transcribed...
Martin T. Swain, Johannes J. Mandel, Werner Dubitz...
ESANN
2003
14 years 11 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
AIPR
2004
IEEE
15 years 1 months ago
Adaptive Road Detection through Continuous Environment Learning
The Intelligent Systems Division of the National Institute of Standards and Technology has been engaged for several years in developing real-time systems for autonomous driving. A...
Mike Foedisch, Aya Takeuchi