Data provided by National Institute of Standards and Technology
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.
About this Dataset
Updated: 2026-09-19
Metadata Last Updated:
2025-01-31 00:00:00
Date Created:
N/A
Data Provided by:
Dataset Owner:
N/A
| Title | Training and Validation Datasets for Neural Network to Fill in Missing Data in EBSD Maps |
|---|---|
| Description | 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. |
| Modified | 2025-01-31 00:00:00 |
| Publisher Name | National Institute of Standards and Technology |
| Contact | mailto:[email protected] |
| Keywords | Electron backscatter diffusion (EBSD) maps , training data , neural networks , image inpainting |
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"title": "Training and Validation Datasets for Neural Network to Fill in Missing Data in EBSD Maps",
"description": "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 \nEmmanuel Atindama, Conor Miller-Lynch, Huston Wilhite, Cody Mattice, G\u00fcnay Do\u011fan, and Prashant Athavale. \nThe EBSD maps were used to train, test, and validate a neural network algorithm to fill in missing data points in a given EBSD map.\nThe 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.",
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