PATENT CLAIM ANALYSIS

Application Number: 16082103
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-07
Patent Classification: ["382", "141000"]

Abstract:
A method of board lumber (Table 2) grading is performed in an industrial environment on a machine learning framework ( 12 ) configured as an interface to a machine learning-based deep convolutional network ( 20 ) that is trained end-to-end, pixels-to-pixels on semantic segmentation. The method uses deep learning techniques that are applied to semantic segmentation to delineate board lumber characteristics (Table 1), including their sizes and boundaries.

Claim (Index 11):
The method of  claim 1 , in which the solution is derived for grading board lumber that is inspected in an industrial environment.

Metadata:
- Claim Count in Document: 3.0
- Percentile: 97.0
- Lexical Diversity: 1.46154
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['10854930', '15352821', '11314852', '15690037', '11316046']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.295031976223584
- 35 USC 102 Novelty (BERT): 0.4959835464100884
- Combined Prediction Score: 0.3151271332422345
- Mean Citation Score: 157.11545200000003
- Max Citation Score: 166.22716
- Similarity Product: 107.36055623702526

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