PATENT CLAIM ANALYSIS

Application Number: 16281971
Application Type: Utility
Filing Date: 2019-02
Publication Date: 2019-08
Patent Classification: ["382", "158000"]

Abstract:
A method of identifying and recognizing characters using a dual-stage neural network pipeline, the method including: receiving, by a computing device, image data; providing the image data to a first convolutional layer of a convolutional neural network (CNN); applying, using the CNN, pattern recognition to the image data to identify a region of the image data containing text; providing sub-image data comprising the identified region of the image data to a convolutional recurrent neural network (CRNN); and recognizing, using the CRNN, the characters within the sub-image data.

Claim (Index 18):
The system of  claim 9 , wherein the CNN comprises:\n a first convolutional layer, a second convolutional layer, first and second rectifier layers respectively following the first and second convolutional layer, first and second pooling layers respectively following the first and second rectifier layers, a sigmoid layer following the second pooling layer, a dropout layer following the sigmoid layer, and three fully-connected layers following the dropout layer.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 99.0
- Lexical Diversity: 2.26087
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15904964', '15491902', '15820253', '15524944', '15697454']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3526605000212783
- 35 USC 102 Novelty (BERT): 0.5666991223627847
- Combined Prediction Score: 0.3740643622554289
- Mean Citation Score: 248.893166
- Max Citation Score: 474.01093
- Similarity Product: 355.15669877815424

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