18482209. OPTICAL INSPECTION-BASED AUTOMATIC DEFECT CLASSIFICATION (Applied Materials, Inc.)
OPTICAL INSPECTION-BASED AUTOMATIC DEFECT CLASSIFICATION
Organization Name
Inventor(s)
Navneet Kumar Singh of Fremont CA US
Arun Ramaswamy Srivatsa of Fremont CA US
Sachin Dangayach of San Jose CA US
Zvi Hersh Goldshtein of Sunnyvale CA US
Rahul Reddy Komatireddi of Hyderabad IN
Yen-Tien Wu of Castro Valley CA US
OPTICAL INSPECTION-BASED AUTOMATIC DEFECT CLASSIFICATION
This abstract first appeared for US patent application 18482209 titled 'OPTICAL INSPECTION-BASED AUTOMATIC DEFECT CLASSIFICATION
Original Abstract Submitted
Implementations disclosed describe, among other things, a systems and techniques for perform efficient inspection of a semiconductor manufacturing sample. The techniques include collecting optical inspection data for training sample(s) that have a plurality of defects. The techniques further include generating, using the optical inspection data, a training data set that includes descriptions, images, and ground truth classifications for the defects. The techniques further include using the training data set to train a plurality of machine learning (ML) classifiers to generate predicted classifications for the defects in the training sample(s). The techniques further include selecting, using the predicted classifications and the ground truth classifications, one or more ML classifiers that meet one or more accuracy criteria, and using the selected ML classifier(s) to classify defects in the semiconductor manufacturing sample.
- Applied Materials, Inc.
- Navneet Kumar Singh of Fremont CA US
- Arun Ramaswamy Srivatsa of Fremont CA US
- Sachin Dangayach of San Jose CA US
- Zvi Hersh Goldshtein of Sunnyvale CA US
- Rahul Reddy Komatireddi of Hyderabad IN
- Sutapa Dutta of Kolkata IN
- Arv Nagpal of Bengaluru IN
- Yen-Tien Wu of Castro Valley CA US
- G06T7/00
- CPC G06T7/0004