Showing 3 open source projects for "cite"

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    Euler Pole Calculator (EPC)

    Euler Pole Calculator (EPC)

    A Matlab software to estimate Euler pole parameters

    The EPC software calculates velocities for any points located on the earth’s surface given the Euler pole parameters and estimates the Euler pole parameters given the observed velocities of a set of sites located on a tectonic plate. Since version 2, the software is able to estimate or apply the Plate Translation Rates, as well. Please cite one of the following papers when you use the software: - Goudarzi, M A, Cocard, M, and Santerre, R. 2014."EPC: Matlab Software to Estimate Euler Pole Parameters". GPS Solutions 18 (1): 153–62. DOI: 10.1007/s10291-013-0354-4*. - Goudarzi, M A. 2025."Evaluating Euler Pole Parameters for the North American Terrestrial Reference Frame of 2022". ...
    Downloads: 2 This Week
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  • 2
    Phenalysis

    Phenalysis

    Analyze agronomic plant research plots in aerial orthomosaic images.

    A graphical user interface to import, analyze and export plots from orthomosaic images of agronomic trials. Please cite the following reference in your work if you use Phenalysis: Khan Z and Miklavcic SJ (2019) An Automatic Field Plot Extraction Method From Aerial Orthomosaic Images. Front. Plant Sci. 10:683. doi: https://doi.org/10.3389/fpls.2019.00683 This tool is being developed through the sponsorship of the Australian Research Council's Industrial Transformation Research Hub on Wheat in a Hot and Dry Climate. ...
    Downloads: 0 This Week
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  • 3

    SPAWNN

    SPatial Analysis With self-organizing Neural Networks

    The SPAWNN toolkit is an innovative toolkit for spatial analysis with self-organizing neural networks which is particularily useful for spatial analysis, visualization and geographical data mining. To run the toolkit, simply download and execute (double-click) the jar-file. Please cite: - Hagenauer, J., & Helbich, M. (2016). SPAWNN: A Toolkit for SPatial Analysis With Self-Organizing Neural Networks. Transactions in GIS, 20(5), 755-775. Other related publications: - Hagenauer, J. (2016). Weighted merge context for clustering and quantizing spatial data with self-organizing neural networks. Journal of Geographical Systems, 18(1), 1-15...
    Downloads: 0 This Week
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