PATENT CLAIM ANALYSIS

Application Number: 15896060
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-10
Patent Classification: ["356", "237500"]

Abstract:
Methods and systems for detecting defects in patterns formed on a specimen are provided. One system includes one or more components executed by one or more computer subsystems, and the component(s) include first and second learning based models. The first learning based model generates simulated contours for the patterns based on a design for the specimen, and the simulated contours are expected contours of a defect free version of the patterns in images of the specimen generated by an imaging subsystem. The second learning based model is configured for generating actual contours for the patterns in at least one acquired image of the patterns formed on the specimen. The computer subsystem(s) are configured for comparing the actual contours to the simulated contours and detecting defects in the patterns formed on the specimen based on results of the comparing.

Claim (Index 10):
The system of  claim 1 , wherein the one or more computer subsystems are further configured for training the first learning based model using a training data set comprising different portions of at least one training design for at least one training specimen and corresponding contour information extracted from training images of the at least one training specimen with a ground truth method.

Metadata:
- Claim Count in Document: 41.0
- Percentile: 88.0
- Lexical Diversity: 2.32308
- Patent Class: 356.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15402094', '15402197', '15402169', '15176139', '15353210']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7267607208844116
- 35 USC 102 Novelty (BERT): 0.5017804528525766
- Combined Prediction Score: 0.704262694081228
- Mean Citation Score: 274.44617400000004
- Max Citation Score: 287.2504
- Similarity Product: 227.547345001936

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test