PATENT CLAIM ANALYSIS

Application Number: 16432874
Application Type: Utility
Filing Date: 2019-06
Publication Date: 2019-09
Patent Classification: ["382", "159000"]

Abstract:
Systems and methods for training and using an image classifier are provided. A plurality of points can be generated from respective patches of images annotated as either a first type or a second type. The points corresponding to the images of the second type can be clustered into two clusters. A first cluster of the two clusters can be identified as closer to the points corresponding to the images annotated as the first type. The points in the first cluster can be assigned to a class positive, the points in the second cluster can be assigned to a class negative, and the points corresponding to the images annotated as the first type can be assigned to an anchor class. A plurality of triplets can be generated based on the points in the various classes. Parameters of an image classifier can be adjusted based on a loss function of the triplets.

Claim (Index 2):
The method of  claim 1 , wherein each patch is represented by image data in a multi-dimensional space, the method further comprising generating, by the device, the plurality of points by converting the image data for each of the patches to a lower-dimensional space using the image classifier.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 100.0
- Lexical Diversity: 2.74138
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['12683124', '14602494', '13567309', '13198382', '13803334']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3186363953488285
- 35 USC 102 Novelty (BERT): 0.4864155211714915
- Combined Prediction Score: 0.3354143079310948
- Mean Citation Score: 192.733902
- Max Citation Score: 212.1668
- Similarity Product: 154.9333263055086

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