Showing 5 open source projects for "matlab genetic algorithm"

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    Swift AI

    Swift AI

    The Swift machine learning library

    Swift AI is a high-performance deep learning library written entirely in Swift. We currently offer support for all Apple platforms, with Linux support coming soon. Swift AI includes a collection of common tools used for artificial intelligence and scientific applications. A flexible, fully-connected neural network with support for deep learning. Optimized specifically for Apple hardware, using advanced parallel processing techniques. We've created some example projects to demonstrate the...
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  • 2
    CRFasRNN

    CRFasRNN

    Semantic image segmentation method described in the ICCV 2015 paper

    ...Our work allows computers to recognize objects in images, what is distinctive about our work is that we also recover the 2D outline of objects. Currently we have trained this model to recognize 20 classes. This software allows you to test our algorithm on your own images – have a try and see if you can fool it, if you get some good examples you can send them to us. CRF-RNN has been developed as a custom Caffe layer named MultiStageMeanfieldLayer. Usage of this layer in the model definition prototxt file looks the following. Check the matlab-scripts or the python-scripts folder for more detailed examples.
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  • 3
    OpenAIL

    OpenAIL

    Open Artificial Intelligence Library

    [Open Artificial Intelligence Library]. This library main goal is to provide a tool box to those who want to use algorithm such as neural network or genetics Algorithm and all algorithms that are commonly within the Artificial Intelligence field.
    Downloads: 0 This Week
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  • 4
    cCNN

    cCNN

    A fast implementation of LeCun's convolutional neural network

    Code of this library is partialy based on myCNN MATLAB class written by Nikolay Chemurin.
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  • 5
    NeuroDraughts is a Draughts/Checkers game that teaches itself how to play through self play. It combines an Artificial Neural Network, trained by Temporal Difference Learning using some Genetic Algorithm style behaviour.
    Downloads: 0 This Week
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