NETL RDE Image Classification Dataset 2025 - 14 Classes

Johnson, Kristyn; Georgieva, Sophia

doi:10.18141/2588604

Title: NETL RDE Image Classification Dataset 2025 - 14 Classes

Dataset
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Abstract

Dataset including high-speed down-axis RDE images used for updated image classification study. This dataset includes 180,000 images with 14 classifications: 1CW, 1CCW, 2CW, 2CCW, 3CW, 3CCW, Deflagration, 4CW, 4CCW, 5CW, and 5CCW. Images are cropped to center annulus, and resized to 301x301 pixels. Images are filtered using the AFRL Beta correction factor.

Authors:

Johnson, Kristyn; Georgieva, Sophia

National Energy Technology Laboratory

Publication Date:: Tue Sep 16 00:00:00 EDT 2025

Research Org.:: NETL

Sponsoring Org.:: USDOE Office of Fossil Energy (FE)

Subject:: Dataset; IP; Machine Learning; Rotating Detonation Engine

OSTI Identifier:: 2588604

DOI:: https://doi.org/10.18141/2588604

Citation Formats


                    Johnson, Kristyn, and Georgieva, Sophia. NETL RDE Image Classification Dataset 2025 - 14 Classes.  United States: N. p., 2025. 
        Web.  doi:10.18141/2588604.

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                    Johnson, Kristyn, & Georgieva, Sophia. NETL RDE Image Classification Dataset 2025 - 14 Classes.  United States.  doi:https://doi.org/10.18141/2588604

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                    Johnson, Kristyn, and Georgieva, Sophia. 2025.  
"NETL RDE Image Classification Dataset 2025 - 14 Classes".  United States.  doi:https://doi.org/10.18141/2588604.  https://www.osti.gov/servlets/purl/2588604. Pub date:Tue Sep 16 00:00:00 EDT 2025

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@article{osti_2588604,

  title        = {NETL RDE Image Classification Dataset 2025 - 14 Classes},

  author       = {Johnson, Kristyn and Georgieva, Sophia},

  abstractNote = {Dataset including high-speed down-axis RDE images used for updated image classification study. This dataset includes 180,000 images with 14 classifications: 1CW, 1CCW, 2CW, 2CCW, 3CW, 3CCW, Deflagration, 4CW, 4CCW, 5CW, and 5CCW. Images are cropped to center annulus, and resized to 301x301 pixels. Images are filtered using the AFRL Beta correction factor.},

  doi          = {10.18141/2588604},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Tue Sep 16 00:00:00 EDT 2025},

  month        = {Tue Sep 16 00:00:00 EDT 2025}

}

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DOI: https://doi.org/10.18141/2588604

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