Showing 6 open source projects for "artificial intelligence algorithm"

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  • 1
    Mars Simulation Project
    The Mars Simulation Project is an open source Java project to create a simulation of future human settlement on the planet Mars. See https://github.com/mars-sim/mars-sim for the LATEST issues/wiki/code change
    Downloads: 4 This Week
    Last Update:
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  • 2
    U-Net Fusion RFI

    U-Net Fusion RFI

    U-Net for RFI Detection based on @jakeret's implementation

    See original code here: https://github.com/jakeret/tf_unet Currently this project is based on Tensorflow 1.13 code base and there are no plans to transfer to TF version 2. The primary improvements to this code base include a training and evaluation framework, along with a fusion based approach to detection, combining a number of models (currently hard coded to two trained models) along with Sum Threshold as an additional "expert." Additional work is being done to add custom layers to...
    Downloads: 0 This Week
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  • 3

    libsombrero

    Astronomical object/structure detection from 1D and 2D data sets.

    Sombrero is a fast wavelet image processing and object detection C library for astronomical images. Sombrero is named after the "Mexican Hat" shape of the wavelet masks used in image convolution and is released under the GNU LGPL library.
    Downloads: 0 This Week
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  • 4
    The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover
    Downloads: 0 This Week
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  • 5
    AstroWeka is a set of extentions to Weka, a popular data mining program, which which allows it to work directly with astronomical data in the Virtual Observatory.
    Downloads: 0 This Week
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  • 6
    The 'BandSystem' spectral analysis system is a rule-based system for the classification of mineral spectra. It consists of a preprocessor, a feature extractor, and a rule-based system to identify minerals from infra-red reflectance spectra.
    Downloads: 0 This Week
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