PATENT CLAIM ANALYSIS

Application Number: 15895759
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2019-08
Patent Classification: ["382", "274000"]

Abstract:
Embodiments disclosed herein involve techniques for automatically retouching photos. A neural network is trained to generate a skin quality map from an input photo. The input photo is separated into high and low frequency layers which are separately processed. A high frequency path automatically retouches the high frequency layer using a neural network that accepts the skin quality map as an input. A low frequency path automatically retouches the low frequency layer using a color transformation generated by a second neural network and the skin quality map. The retouched high and low frequency layers are combined to generate the final output. In some embodiments, a training set for any or all of the networks is enhanced by applying a modification to an original image from a pair of retouched photos in the training set to improve the resulting performance of trained networks over different input conditions.

Claim (Index 5):
The media of  claim 1 , wherein the first neural network operates on patches of the high frequency layer.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 88.0
- Lexical Diversity: 1.97436
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['13683954', '15699691', '11804605', '14912441', '10229275']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3167280222641425
- 35 USC 102 Novelty (BERT): 0.5286550052915171
- Combined Prediction Score: 0.33792072056688
- Mean Citation Score: 210.59326
- Max Citation Score: 242.87273
- Similarity Product: 118.10517756806104

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