PATENT CLAIM ANALYSIS

Application Number: 16265417
Application Type: Utility
Filing Date: 2019-02
Publication Date: 2019-05
Patent Classification: ["382", "159000"]

Abstract:
A set of virtual images can be generated based on one or more real images and target rendering specifications, such that the set of virtual images correspond to (for example) different rendering specifications (or combinations thereof) than do the real images. An image style can be transferred to the at least some of the virtual images of the set of virtual images to generate a stylized virtual image. A machine-learning model can be trained using a plurality of stylized virtual images. Another real image can then be processed using the trained machine-learning model. The processing can include segmenting the other real image to detect whether and/or which objects are represented (and/or a state of the object). The object data can then be used to identify (for example) a state of a procedure.

Claim (Index 3):
The method of  claim 1 , further comprising:\n availing a set of style images to an encoder; encoding the set of style images to produce a set of style feature representations; and generating a reconstructed covariance based on the set of style feature representations; wherein transferring the image style includes generating the stylized virtual image using the virtual image and the reconstructed covariance.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 99.0
- Lexical Diversity: 2.1
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15997408', '15174628', '15476205', '15444583', '15970831']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.256863737877323
- 35 USC 102 Novelty (BERT): 0.5233754634563105
- Combined Prediction Score: 0.2835149104352217
- Mean Citation Score: 166.48781200000005
- Max Citation Score: 301.7568
- Similarity Product: 205.62346890449524

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