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    • Training and Validation Datasets for Neural Network to Fill in Missing Data in EBSD Maps

    Metadata Updated: September 30, 2025

    This dataset consists of the synthetic electron backscatter diffraction (EBSD) maps generated for the paper, titled "Hybrid Algorithm for Filling in Missing Data in Electron Backscatter Diffraction Maps" by Emmanuel Atindama, Conor Miller-Lynch, Huston Wilhite, Cody Mattice, Günay Doğan, and Prashant Athavale. The EBSD maps were used to train, test, and validate a neural network algorithm to fill in missing data points in a given EBSD map.The dataset includes 8000 maps for training, 1000 maps for testing, 2000 maps for validation. The dataset also includes noise-added versions of the maps, namely, one more map per each clean map.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: See this page for license information.

    Downloads & Resources

    Dates

    Metadata Created Date September 30, 2025
    Metadata Updated Date September 30, 2025
    Data Update Frequency irregular

    Metadata Source

    Harvested from Commerce Non Spatial Data.json Harvest Source

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date September 30, 2025
    Metadata Updated Date September 30, 2025
    Publisher National Institute of Standards and Technology
    Maintainer
    Identifier ark:/88434/mds2-3694
    Data First Published 2025-03-24
    Language en
    Data Last Modified 2025-01-31 00:00:00
    Category Materials:Materials characterization, Materials:Modeling and computational material science, Mathematics and Statistics:Image and signal processing, Metrology:Electrical/electromagnetic metrology, Information Technology:Data and informatics
    Public Access Level public
    Data Update Frequency irregular
    Bureau Code 006:55
    Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Harvest Object Id 9f3ccfce-ff2b-4e2f-aa7a-1a8e63d887f2
    Harvest Source Id bce99b55-29c1-47be-b214-b8e71e9180b1
    Harvest Source Title Commerce Non Spatial Data.json Harvest Source
    Homepage URL https://data.nist.gov/od/id/mds2-3694
    License https://www.nist.gov/open/license
    Program Code 006:045
    Source Datajson Identifier True
    Source Hash 2ae92bfaa14794bfe24f240d639de5e8d83051f6ddae56614172cc498b584e1e
    Source Schema Version 1.1

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