PATENT CLAIM ANALYSIS

Application Number: 16086646
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-03
Patent Classification: ["382", "156000"]

Abstract:
In a method of converting an input image patch to a text output, a convolutional neural network (CNN) is applied to the input image patch to estimate an n-gram frequency profile of the input image patch. A computer-readable database containing a lexicon of textual entries and associated n-gram frequency profiles is accessed and searched for an entry matching the estimated frequency profile. A text output is generated responsively to the matched entries.

Claim (Index 3):
The method according to  claim 1 , wherein at least one of said n-grams is a sub-word.

Metadata:
- Claim Count in Document: 53.0
- Percentile: 97.0
- Lexical Diversity: 1.69565
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16132518', '15963990', '14813233', '15883112', '16040275']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3456488049102227
- 35 USC 102 Novelty (BERT): 0.501502829764177
- Combined Prediction Score: 0.3612342073956182
- Mean Citation Score: 185.257804
- Max Citation Score: 202.55704
- Similarity Product: 123.74956606225967

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