PATENT CLAIM ANALYSIS

Application Number: 16363354
Application Type: Utility
Filing Date: 2019-03
Publication Date: 2019-09
Patent Classification: ["706", "025000"]

Abstract:
The present invention relates generally to object annotation, specifically to polygonal annotations of objects. Described are methods of annotating an object including steps of receiving an image depicting an object, generating a set of image features using a CNN encoder implemented on one or more computers, and producing a polygon object annotation via a recurrent decoder or a Graph Neural Network. The recurrent decoder may include a recurrent neural network, a graph neural network or a gated graph neural network. A system for annotating an object and a method of training an object annotation system are also described.

Claim (Index 7):
The method of  claim 2 , wherein producing each polygon prediction of the set of polygon predictions includes a series of timesteps to produce a set of vertex predictions defining the polygon prediction and the evaluator network is applied at each timestep of the series of timesteps.

Metadata:
- Claim Count in Document: 17.0
- Percentile: 99.0
- Lexical Diversity: 1.76667
- Patent Class: 706.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15715400', '15710821', '15817161', '15815686', '15885667']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3882987309617424
- 35 USC 102 Novelty (BERT): 0.490818141167073
- Combined Prediction Score: 0.3985506719822755
- Mean Citation Score: 187.32879599999995
- Max Citation Score: 198.25957
- Similarity Product: 131.45751967595638

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