WM811k Silicon Wafer Map Dataset Image
- kaggle.com
zipUpdated Dec 20, 2024
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EmailClick to copy linkLink copiedCiteMuhammad Junayed (2024). WM811k Silicon Wafer Map Dataset Image [Dataset]. https://www.kaggle.com/datasets/muhammedjunayed/wm811k-silicon-wafer-map-dataset-imagezip(1006403 bytes)Available download formatsDataset updatedDec 20, 2024AuthorsMuhammad JunayedLicenseAttribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automaticallyDescriptionThis dataset contains a subset of the WM811k Silicon Wafer Map Dataset originally taken from http://mirlab.org/dataSet/public/, designed for defect classification in semiconductor manufacturing. The dataset is organized into nine defect categories and is complemented by a MATLAB implementation of a Convolutional Neural Network (CNN) for defect recognition.
It supports research on identifying and classifying manufacturing defects in silicon wafers. The dataset is part of the research presented in the paper: Enhancing Defect Recognition: Convolutional Neural Networks for Silicon Wafer Map Analysis
📄 Read the Paper on IEEE Xplore DOI: 10.1109/ICAEEE62219.2024.10561853
Key Features Defect Categories: Center, Donut, Edge Local, Edge Ring, Local, Near Full, None, Random, Scratch.
Image Format: 32x32 pixels .png images.
Total Images: 902 (sampled subset of WM811k).
WM-811k Augmented&Preprossed
- kaggle.com
zipUpdated Mar 14, 2024ShareFacebookTwitterEmailClick to copy linkLink copiedCiteNithinBandi (2024). WM-811k Augmented&Preprossed [Dataset]. https://www.kaggle.com/datasets/nithinbandi/wm-811k-augmented-and-preprossedzip(324290612 bytes)Available download formatsDataset updatedMar 14, 2024AuthorsNithinBandiLicenseMIT Licensehttps://opensource.org/licenses/MIT
License information was derived automaticallyDescriptionOriginal Datset : http://mirlab.org/dataset/public/
https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F17663268%2F04d76e0ccd2932bd49d35efbbdd5ecac%2Fdownload.jpeg?generation=1710476490893730&alt=media" alt="">
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Synthesized Multi-GFA Multi-bin Wafer Bin Map Dataset
- ieee-dataport.org
Updated Apr 21, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteDong Ni (2022). Synthesized Multi-GFA Multi-bin Wafer Bin Map Dataset [Dataset]. https://ieee-dataport.org/documents/synthesized-multi-gfa-multi-bin-wafer-bin-map-datasetDataset updatedApr 21, 2022AuthorsDong NiLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyDescriptionThis dataset contains 1050 multi-pattern multi-bin wafer bin maps (WBMs) synthesized from WM-811K binary WBM dataset and real world multi-bin WBMs using a trained pix2pix model.
wm811k-wafer-map-images
- kaggle.com
zipUpdated Jul 5, 2020ShareFacebookTwitterEmailClick to copy linkLink copiedCiteRajan Jha (2020). wm811k-wafer-map-images [Dataset]. https://www.kaggle.com/iamrajanjha/wm811kwafermapimageszip(1141460846 bytes)Available download formatsDataset updatedJul 5, 2020AuthorsRajan JhaDescriptionDataset
This dataset was created by Rajan Jha
Contents
WM811K without 'none' and '[0 0]'
- kaggle.com
zipUpdated Sep 18, 2023ShareFacebookTwitterEmailClick to copy linkLink copiedCiteNewerZeus (2023). WM811K without 'none' and '[0 0]' [Dataset]. https://www.kaggle.com/datasets/newerzeus/wm811k-without-none-and-0-0zip(209813078 bytes)Available download formatsDataset updatedSep 18, 2023AuthorsNewerZeusDescriptionDataset
This dataset was created by NewerZeus
Contents
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WM811k Silicon Wafer Map Dataset with Defect Detection
Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically
This dataset contains a subset of the WM811k Silicon Wafer Map Dataset originally taken from http://mirlab.org/dataSet/public/, designed for defect classification in semiconductor manufacturing. The dataset is organized into nine defect categories and is complemented by a MATLAB implementation of a Convolutional Neural Network (CNN) for defect recognition.
It supports research on identifying and classifying manufacturing defects in silicon wafers. The dataset is part of the research presented in the paper: Enhancing Defect Recognition: Convolutional Neural Networks for Silicon Wafer Map Analysis
📄 Read the Paper on IEEE Xplore DOI: 10.1109/ICAEEE62219.2024.10561853
Key Features Defect Categories: Center, Donut, Edge Local, Edge Ring, Local, Near Full, None, Random, Scratch.
Image Format: 32x32 pixels .png images.
Total Images: 902 (sampled subset of WM811k).