Synthetic Semiconductor Wafer Micro-Defect Detection Dataset
收藏Zenodo2026-06-10 更新2026-06-12 收录
下载链接：
https://zenodo.org/doi/10.5281/zenodo.20633424
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资源简介：
This dataset contains synthetic grayscale images of semiconductor wafers with periodic circuit patterns, designed for unsupervised anomaly detection benchmarking in computer vision.
The training set contains 200 normal (non-defective) wafers. The test set contains 100 wafers (50 normal, 50 defective). Defects are subtle phase perturbations in the periodic pattern that are invisible in the raw spatial domain and require frequency-domain analysis (2D FFT) to detect.
Generation method: Python 3.11 with NumPy and PIL. Fully reproducible with fixed random seed (42).
Files:
- train/ : 200 normal images (256×256 PNG)
- test/ : 100 images (50 normal, 50 defective)
- train.csv : Training labels
- test_answers.csv : Ground truth
- generate_dataset.py : Reproducible generation script
License: CC BY 4.0 (Commercial use allowed)
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Zenodo创建时间：
2026-06-10
