Detecting outliers and anomalies for OCD metrology machine learning
US12038271B2 · kind B2 · utility
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17Claims
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Key dates
| Filing date | Jan 7, 2021 |
| Grant date | Jul 16, 2024 |
| Priority date | — |
| Expiry date | Jan 7, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01N2021/8883
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
A system and methods for OCD metrology are provided including receiving training data for training an OCD machine learning (ML) model, including multiple pairs of corresponding sets of scatterometric data and reference parameters. For each of the pairs, one or more corresponding outlier metrics are by calculated and corresponding outlier thresholds are applied whether a given pair is an outlier pair. The OCD MIL model is then trained with the training data less the outlier pairs.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.