PATENT CLAIM ANALYSIS

Application Number: 16376877
Application Type: Utility
Filing Date: 2019-04
Publication Date: 2020-01
Patent Classification: ["709", "203000"]

Abstract:
A method for enhancing quality of media transmitted via network uses an AI enhancing model built-in the client device to enhance the quality of video streams received from network. The AI enhance module is pre-trained by using a neural network in the server to analyze differences between the decoded images and the raw images that are generated by the server. Wherein, the AI enhance module enhances decoded images by using algorithms which are defined by analyzing differences between the decoded images and the raw images that are generated by the server. Such that, the enhanced images are visually more similar to the raw images than the decoded images do.

Claim (Index 18):
The method of  claim 16 , wherein, in the step of using a compare module to compare, the compare module employs a discriminator to compare the differences between the training output image and its corresponding training raw image for converging Generative Adversarial Networks (GAN) loss and modifying said training weighted parameters.

Metadata:
- Claim Count in Document: 59.0
- Percentile: 100.0
- Lexical Diversity: 1.94915
- Patent Class: 709.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16027022', '15417056', '15871945', '15703896', '16254448']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2346629085043397
- 35 USC 102 Novelty (BERT): 0.6007349039144656
- Combined Prediction Score: 0.2712701080453523
- Mean Citation Score: 245.868822
- Max Citation Score: 533.9403
- Similarity Product: 454.52020916669375

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