Showing 6 open source projects for "image pattern recognition"

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  • 1
    Java Neural Network Framework Neuroph
    Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use.
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    Downloads: 38 This Week
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  • 2

    DGRLVQ

    Dynamic Generalized Relevance Learning Vector Quantization

    Some of the usual problems for Learning vector quantization (LVQ) based methods are that one cannot optimally guess about the number of prototypes required for initialization for multimodal data structures i.e.these algorithms are very sensitive to initialization of prototypes and one has to pre define the optimal number of prototypes before running the algorithm. If a prototype, for some reasons, is ‘outside’ the cluster which it should represent and if there are points of a different...
    Downloads: 0 This Week
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  • 3

    libVMR

    VMR - machine learning library

    ...libVMR is based on the most popular neural network model with a higher generalization ability from kernel tricks - vector machine by Reshetov (VMR). The library has been designed to learn from data sets. Typical applications here are pattern recognition ( binary classification).
    Downloads: 0 This Week
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  • 4

    NN Image Recognition (with source-code)

    This is ANN trained application to predict digits from 0 - 9.

    It can predict digits from 0-9 with Artificial Neural Network. I trained ANN with 100 samples of each digit. It takes input of 20x20 pixel image and predicts it with Neural Network. It may predict wrong digit due to very low sample data but it work 90% correctly. Note: JRE 1.6 is required to run this application.
    Downloads: 0 This Week
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  • 5
    This is an attempt to create simple image recognition program in java. Demo here: http://www.youtube.com/watch?v=N4m4j4D3pJU
    Downloads: 0 This Week
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  • 6
    Data Mining Platform is a platform for data mining and analysis. It contains many of the new and sophisticated methods such as kernel-based classification, two-way clustering, bayesian networks, pattern recognition for time series analysis and many other
    Downloads: 0 This Week
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