PATENT CLAIM ANALYSIS

Application Number: 16222092
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-09
Patent Classification: ["382", "181000"]

Abstract:
A system and method for identifying a subject based upon ear recognition using a convolutional neural network (CNN) and handcrafted features, wherein an ear in an image is cropped using ground truth annotations and landmark detection is performed to obtain the information required to normalize pose and scale variations. The normalized images are then described by different feature extractors and matched through distance metrics. Finally, scores are fused and a subject identification decision is made.

Claim (Index 6):
The method of  claim 1 , further comprising normalizing the CNN-learned matching scores and the handcrafted matching scores prior to fusing the CNN-learned matching scores and the handcrafted matching scores.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 98.0
- Lexical Diversity: 1.28125
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15689046', '14555477', '15120287', '11708558', '15936525']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3034731300873218
- 35 USC 102 Novelty (BERT): 0.4891778956689119
- Combined Prediction Score: 0.3220436066454808
- Mean Citation Score: 175.36137
- Max Citation Score: 203.76598
- Similarity Product: 141.44402765548946

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

Dataset: test