PATENT CLAIM ANALYSIS

Application Number: 15863138
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2019-07
Patent Classification: ["382", "128000"]

Abstract:
A system and method includes acquisition of a plurality of sets of body surface data, first data indicating locations of a first one or more body landmarks for each of the plurality of sets of body surface data, and second data indicating locations of a second one or more body landmarks for each of the plurality of sets of body surface data, training, using the plurality of sets of body surface data and data indicating locations of the first one or more body landmarks for each of the plurality of sets of body surface data, of a first reinforcement learning network to identify the first one or more body landmarks based on body surface data, and training, using the plurality of sets of body surface data and data indicating locations of the second one or more body landmarks for each of the plurality of sets of body surface data, of a second reinforcement learning network to identify the second one or more body landmarks based on body surface data.

Claim (Index 6):
A system according to  claim 1 , wherein the training of the first reinforcement learning network, the second reinforcement learning network and the third reinforcement learning network is contemporaneous, and the processing unit further to execute processor-executable program code to:\n input a set of surface data associated with a body to the trained first reinforcement learning network; input the set of surface data associated with the body to the trained second reinforcement learning network; input the set of surface data associated with the body to the trained third reinforcement learning network; determine, using the trained first reinforcement learning network, the first one or more body landmark locations of the body; determine, using the trained second reinforcement learning network, the second one or more body landmark locations of the body; and determine, using the trained third reinforcement learning network, the third one or more body landmark locations of the body.

Metadata:
- Claim Count in Document: 21.0
- Percentile: 86.0
- Lexical Diversity: 5.08571
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15695112', '15591157', '15386856', '15689046', '13867560']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3345112038602046
- 35 USC 102 Novelty (BERT): 0.486456924401069
- Combined Prediction Score: 0.3497057759142911
- Mean Citation Score: 171.78122000000005
- Max Citation Score: 182.06818
- Similarity Product: 125.16481987902404

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test