Showing 36 open source projects for "gnu-efi"

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  • 1
    Yann
    Yann is Yet Another Neural Network. Yann is a library to create fast neural networks. It is also a GUI to easily create, edit, train, execute and investigate networks. Multiple topologies, runtime properties and ensemble learning are supported.
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  • 2
    With miao3d you can train a specific Gaussian Markov Random Field (GMRF) that then can be used to estimate a depthmap ("3D"), given an image ("2D"). A GUI allows inspection of the image + depthmap.
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  • 3
    Isolation Forest detects data-anomalies using binary trees. Platform: R (www.r-project.org) Reference: Fei Tony Liu, Kai Ming Ting, and Zhi-Hua Zhou, “Isolation Forest”, IEEE International Conference on Data Mining 2008 (ICDM 08)
    Downloads: 2 This Week
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  • 4
    A graphical MatLab framework for estimating the parameters of, modeling and simulating static and dynamic linear and polynomial systems in the errors-in-variables context with the intent of comparing various estimation strategies.
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  • 5
    Weekend-robotics enables the dedicated amateur to build a autonomous robot. It runs on a Linux system for high-level operations and offers an interface to the defacto standard hardware abstraction layer in robotics, Player/Stage.
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  • 6
    ANT is a lightweight implementation in C of a kind of artificial neural net called Multilayer Perceptron, which uses the backpropagation algorithm as learning method. The package includes an introductory example to start using artificial neural nets.
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  • 7

    TimeSleuth - Temporal Rule Discovery

    Temporal and Causal Decision Rules

    TimeSleuth discovers temporal decision rules. It also judges the (a)causality of the rules. TimeSleuth can discover rules that involve time: {if (rainy_yesterday = true) then rainy_today = true}, or {if (rainy_tomorrow = true) then rainy_today = true}.
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  • 8

    Betelgeuse

    Powerful machine learning modeling software suitable for industry use.

    Betelgeuse is a machine learning modeling package designed to meet the requirements of heavy-duty industry use. It was designed to be efficient, reliable, and highly modular; it is developed primarily in Python to promote maintainability and rapid development, but uses Cython and C in critical bottlenecks for efficiency. It focuses on high-quality implementations of a diverse set of the most widely used machine learning algorithms. An important goal of Betelgeuse is to have a clean,...
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  • 9
    Wa (word analysis) engine is a engine implementing common IA algorithms such as in-depth tree search using alpha-beta.
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  • 10
    A fast kernel density estimation based classifier. Uses multi resolution KD trees to significantly reduce the number of calculations needed to perform density estimation.
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  • 11
    a distributed engine for abstract neural network development via natural-language programming
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