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    ESANN
    2003
    66views Neural Networks» more  ESANN 2003»
    Meter value recognition using locally connected hierarchical networks
    13 years 6 months ago
    Meter value recognition using locally connected hierarchical networks
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    This paper describes a two-stage system for the recognition ge meter values. A feed-forward Neural Abstraction Pyramid is initialized in an unsupervised manner and trained in a sup...
    Sven Behnke
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    ESANN
    2003
    142views Neural Networks» more  ESANN 2003»
    Comparison of neural algorithms for blind source separation in sensor array applications
    13 years 6 months ago
    Comparison of neural algorithms for blind source separation in sensor array applications
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    - A test bed of experiments with real and artificially generated data has been designed to compare the performance of three well-known algorithms for BSS. The main goal of these ex...
    Guillermo Bedoya, Sergio Bermejo, Joan Cabestany
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    ESANN
    2003
    112views Neural Networks» more  ESANN 2003»
    VLSI Realization of a Two-Dimensional Hamming Distance Comparator ANN for Image Processing Applications
    13 years 6 months ago
    VLSI Realization of a Two-Dimensional Hamming Distance Comparator ANN for Image Processing Applications
    Download  lsmwww.epfl.ch
    This paper presents the hardware realization of a Hamming artificial neural network, and demonstrates its use in a high-speed precision alignment system. High degree of parallelism...
    Stéphane Badel, Alexandre Schmid, Yusuf Leb...
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    ESANN
    2003
    65views Neural Networks» more  ESANN 2003»
    Robust Topology Representing Networks
    13 years 6 months ago
    Robust Topology Representing Networks
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    Martinetz and Schulten proposed the use of a Competitive Hebbian Learning (CHL) rule to build Topology Representing Networks. From a set of units and a data distribution, a link i...
    Michaël Aupetit
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    ESANN
    2003
    82views Neural Networks» more  ESANN 2003»
    High-dimensional labeled data analysis with Gabriel graphs
    13 years 6 months ago
    High-dimensional labeled data analysis with Gabriel graphs
    Download  www.dice.ucl.ac.be
    We propose the use of the Gabriel graph for the exploratory analysis of potentially high dimensional labeled data. Gabriel graph is a subgraph of the Delaunay triangulation, which ...
    Michaël Aupetit
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    ESANN
    2003
    92views Neural Networks» more  ESANN 2003»
    On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures
    13 years 6 months ago
    On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures
    Download  www.dice.ucl.ac.be
    Efficient probability density function estimation is of primary interest in statistics. A popular approach for achieving this is the use of finite Gaussian mixture models. Based on...
    Cédric Archambeau, John Aldo Lee, Michel Ve...
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    ESANN
    2003
    98views Neural Networks» more  ESANN 2003»
    A Fuzzy ARTMAP Probability Estimator with Relevance Factor
    13 years 6 months ago
    A Fuzzy ARTMAP Probability Estimator with Relevance Factor
    Download  www.dice.ucl.ac.be
    Abstract. An incremental, nonparametric probability estimation procedure using a variation of the Fuzzy ARTMAP (FAM) neural network is introduced. The resulted network, called Fuzz...
    Razvan Andonie, Lucian Sasu
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    ESANN
    2003
    85views Neural Networks» more  ESANN 2003»
    The hypersphere neuron
    13 years 6 months ago
    The hypersphere neuron
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    In this paper a special higher order neuron, the hypersphere neuron, is introduced. By embedding Euclidean space in a conformal space, hyperspheres can be expressed as vectors. The...
    Vladimir Banarer, Christian Perwass, Gerald Sommer
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    ESANN
    2003
    136views Neural Networks» more  ESANN 2003»
    Neural Networks and M5 model trees in modeling water level-discharge relationship for an Indian river
    13 years 6 months ago
    Neural Networks and M5 model trees in modeling water level-discharge relationship for an Indian river
    Download  www.dice.ucl.ac.be
    : In flood management it is important to reliably estimate the discharge in a river. Hydrologists use historic data to establish a rating curve – a relationship between the water...
    Biswanath Bhattacharya, Dimitri P. Solomatine
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    ESANN
    2001
    162views Neural Networks» more  ESANN 2001»
    A divide-and-conquer learning architecture for predicting unknown motion
    13 years 6 months ago
    A divide-and-conquer learning architecture for predicting unknown motion
    Download  www.dice.ucl.ac.be
    Time varying environments or model selection problems lead to crucial dilemmas in identification and control science. In this paper, we propose a modular prediction scheme consisti...
    Patrice Wira, Jean-Philippe Urban, Julien Gresser
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