PATENT CLAIM ANALYSIS

Application Number: 16442365
Application Type: Utility
Filing Date: 2019-06
Publication Date: 2019-10
Patent Classification: ["382", "156000"]

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using an image processing neural network system. One of the systems includes a domain transformation neural network implemented by one or more computers, wherein the domain transformation neural network is configured to: receive an input image from a source domain; and process a network input comprising the input image from the source domain to generate a transformed image that is a transformation of the input image from the source domain to a target domain that is different from the source domain.

Claim (Index 20):
The method of  claim 19 , wherein updating current values of the parameters of the domain transformation neural network while holding values of the parameters of the discriminator neural network and values of the parameters of the task neural network fixed comprises:\n determining an update for the current values of the parameters of the domain transformation neural network by performing the neural network training technique to minimize the loss function with respect to the parameters of the domain transformation neural network.

Metadata:
- Claim Count in Document: 18.0
- Percentile: 100.0
- Lexical Diversity: 2.01923
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15633288', '15166164', '15705151', '15179403', '15850007']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3657733217203479
- 35 USC 102 Novelty (BERT): 0.506143031399022
- Combined Prediction Score: 0.3798102926882153
- Mean Citation Score: 246.03973800000003
- Max Citation Score: 255.61539
- Similarity Product: 171.35048551401968

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