Showing 5 open source projects for "mining"

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  • 1
    Dawarich

    Dawarich

    Self-hostable alternative to Google Timeline

    Dawarich is a command-line tool (likely Ruby-based) for transforming and analyzing Arabic text data with normalization, diacritic handling, segmentation, and morphological tokenization. Designed for text mining and NLP workflows in Arabic-language contexts.
    Downloads: 1 This Week
    Last Update:
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  • 2
    GeoDMA

    GeoDMA

    Geographic feature extraction and data mining

    GeoDMA is a plugin for TerraView software, used for geographical data mining. With a single image, the user can perform segmentation, attributes extraction, normalization and classification.
    Downloads: 0 This Week
    Last Update:
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  • 3
    GEOMS2

    GEOMS2

    Geostatistics and geosciences modeling software

    ...Download datasets for students of Geostatistics 2017 (Petroleum Engineering): https://sourceforge.net/projects/geoms2/files/Geostatistics_Petroleum.zip/download Download datasets for students of Geostatistics 2017 (Geology and Mining Engineering): https://sourceforge.net/projects/geoms2/files/Geostatistics_Mining.zip/download Old: http://sourceforge.net/projects/geoms2/files/SETS_geoestatistica2_2015.7z/download https://sites.google.com/site/cmrpsoftware/downloads/Quarry_sets.7z?attredirects=0&d=1 http://sourceforge.net/projects/geoms2/files/Mining.7z/download
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    Downloads: 11 This Week
    Last Update:
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  • 4

    BioRec:Bird Census field data annotation

    Recognizing biological data from a notebook.

    This project helps to digitize field data for a certain Bird Census method. Namely, bird census based on personal inspection or small (~10 km^2) regions with recording birds' position and behaviour on paper. This project makes it easy to annotate such field data and to make this data available for statistical analysis.
    Downloads: 0 This Week
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  • 5

    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. ...
    Downloads: 0 This Week
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