Detection Limits for SEM Image Segmentation
Resources
7 resources available
-
source code for detection limits
FILE -
relationships between AI model accuracy and image quality metrics
URL -
Tabular files with image and AI model metrics
ZIP FILE CONTAINS A FOLDER WITH IMAGE QUALITY METRICS AND A FOLDER WITH AI MODEL ACCURACY -
Six sets of simulated SEM images
ZIP FILE WITH SIX SUBFOLDERS CONTAINING SEM IMAGE COLLECTIONS -
Three trained AI models (U-net architecture)
ZIP CONTAINS THREE FOLDERS WITH TENSORFLOW AI MODELS -
Six masks for the six simulated SEM image collections
ZIP FILE CONTAINS MASK IMAGES AND THE INITIAL INTENSITY IMAGE WITH MAX CONTRAST AND MIN NOISE -
README
TEXT/PLAIN
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| accrualPeriodicity | irregular |
| bureauCode |
[
"006:55"
]
|
| contactPoint |
{
"fn": "Peter Bajcsy",
"hasEmail": "mailto:peter.bajcsy@nist.gov"
}
|
| description | The dataset consists of six collections of SEM images, three trained U-net AI models, and CSV files with image quality metrics and trained AI model accuracy metrics. Each SEM image collection contains images augmented with Poisson noise and contrast.This work was performed with funding from the CHIPS Metrology Program, part of CHIPS for America, National Institute of Standards and Technology, U.S. Department of Commerce. |
| distribution |
[
{
"title": "source code for detection limits",
"accessURL": "https://github.com/usnistgov/detection_limits",
"description": "Python code"
},
{
"title": "relationships between AI model accuracy and image quality metrics",
"format": "URL",
"accessURL": "https://pages.nist.gov/detection_limits/web/index.html",
"description": "graphs"
},
{
"title": "Tabular files with image and AI model metrics",
"format": "zip file contains a folder with image quality metrics and a folder with AI model accuracy",
"mediaType": "application/zip",
"description": "Image quality metrics extracted from six simulated SEM images, as well as three AI model accuracy metrics obtained by evaluating the trained AI models on the sixth of the simulated SEM image collections.",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3838/metrics_sets.zip"
},
{
"title": "Six sets of simulated SEM images",
"format": "zip file with six subfolders containing SEM image collections",
"mediaType": "application/zip",
"description": "SEM images with varying noise and contrast values",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3838/intensity_sets.zip"
},
{
"title": "Three trained AI models (U-net architecture)",
"format": "zip contains three folders with TensorFlow AI models",
"mediaType": "application/zip",
"description": "Three trained AI models on the first five of six simulated SEM image collections",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3838/AImodel_sets.zip"
},
{
"title": "Six masks for the six simulated SEM image collections",
"format": "zip file contains mask images and the initial intensity image with max contrast and min noise",
"mediaType": "application/zip",
"description": "image masks defining foreground and background labels",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3838/mask_sets.zip"
},
{
"title": "README",
"mediaType": "text/plain",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3838/README.txt"
}
]
|
| identifier | ark:/88434/mds2-3838 |
| issued | 2025-06-12 |
| keyword |
[
"AI model",
"SEM",
"detection limits",
"dimensional metrology",
"scanning electron microscopy"
]
|
| landingPage | https://data.nist.gov/od/id/mds2-3838 |
| language |
[
"en"
]
|
| license | https://www.nist.gov/open/license |
| modified | 2025-05-12 00:00:00 |
| programCode |
[
"006:045"
]
|
| publisher |
{
"name": "National Institute of Standards and Technology",
"@type": "org:Organization"
}
|
| theme |
[
"Information Technology:Computational science",
"Mathematics and Statistics:Image and signal processing",
"Mathematics and Statistics:Uncertainty quantification",
"Metrology:Dimensional metrology",
"Nanotechnology:Nanoelectronics"
]
|
| title | Detection Limits for SEM Image Segmentation |
