PATENT CLAIM ANALYSIS

Application Number: 15997408
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-12
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. A machine-learning model can be trained using the set of 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 15):
A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause one or more data processors to perform actions including:\n identifying a set of states represented in a procedural workflow; for each state of the set of states:\n accessing one or more base images that corresponds to the state; and \n generating, for each base image of the one or more base images, first image-segmentation data that indicates a presence and/or location of each of one or more objects within the base image; \n identifying a set of target rendering specifications; generating a set of virtual images based on the set of target rendering specifications and the one or more base images, wherein, for each of the set of states, the set of virtual images includes at least one virtual image based on the base image that corresponds to the state; generating, for each virtual image of the set of virtual images, corresponding data that includes:\n an indication of the state of the set of states with which the virtual image is associated; and \n second image-segmentation data that indicates a presence and/or position of each of one or more objects within the virtual image; \n training a machine-learning model using the set of virtual images and corresponding data to define a set of parameter values; accessing a real image; processing the real image via execution of the trained machine-learning model using the set of parameter values, wherein the processing includes identifying third image-segmentation data that indicates a presence and/or position of each of one or more objects within the real image; generating an output based on the third image-segmentation data; and presenting or transmitting the output.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 94.0
- Lexical Diversity: 1.93443
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15917331', '15893864', '15090984', '15715604', '15906141']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3299705033670433
- 35 USC 102 Novelty (BERT): 0.4676486474996778
- Combined Prediction Score: 0.3437383177803068
- Mean Citation Score: 143.54653000000005
- Max Citation Score: 153.23228
- Similarity Product: 115.65979219472408

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