PATENT CLAIM ANALYSIS

Application Number: 15771577
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2019-03
Patent Classification: ["356", "402000"]

Abstract:
Described herein is a method for predicting visual texture parameters of a paint having a known paint formulation. The visual texture parameters of the paint are determined using an artificial neural network on the basis of a number of color components used in the known paint formulation. The method includes determining a value of at least one characteristic variable describing at least one optical property using a physical model for the known paint formulation. The method also includes assigning the value to the known paint formulation, and transmitting the value to the artificial neural network as an input signal for determining the visual texture parameters. The value describes the at least one optical property for at least some of the number of color components of the known paint formulation. The method further includes training the neural network using a plurality of color originals each having a respective known paint formulation.

Claim (Index 5):
The method as claimed in  claim 1 , wherein a set of parameters that describes at least one optical property of at least some of the number of color components of a respective known paint formulation is selected as a characteristic variable.

Metadata:
- Claim Count in Document: 10.0
- Percentile: 91.0
- Lexical Diversity: 2.53226
- Patent Class: 356.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['12663364', '13613900', '09874697', '11662512', '10037832']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7083967220063752
- 35 USC 102 Novelty (BERT): 0.4705642914742672
- Combined Prediction Score: 0.6846134789531644
- Mean Citation Score: 156.44951999999995
- Max Citation Score: 165.87166000000005
- Similarity Product: 124.8145877066386

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