PATENT CLAIM ANALYSIS

Application Number: 16522399
Application Type: Utility
Filing Date: 2019-07
Publication Date: 2019-11
Patent Classification: ["382", "156000"]

Abstract:
A method of classifying substrates with a metrology tool is herein disclosed. The method begins by training a deep learning framework using convolutional neural networks with a training dataset for classifying image dataset. Obtaining a new image from the meteorology tool. Running the new image through the deep learning framework to classify the new image.

Claim (Index 15):
The non-transitory computer-readable medium of  claim 11  wherein determining from the matching image, quality information regarding the substrate further comprises extracting metadata from the matching image and tagging the metadata to the substrate.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 100.0
- Lexical Diversity: 1.63889
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15635367', '14521345', '15402169', '15236334', '14942738']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3355003730221564
- 35 USC 102 Novelty (BERT): 0.5123268461691887
- Combined Prediction Score: 0.3531830203368596
- Mean Citation Score: 179.11386799999997
- Max Citation Score: 306.73
- Similarity Product: 252.5903381550312

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

Dataset: test