PATENT CLAIM ANALYSIS

Application Number: 15942226
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-10
Patent Classification: ["382", "157000"]

Abstract:
In order for the feature extractors to operate with sufficient accuracy, a high degree of training is required. In this situation, a neural network implementing the feature extractor may be trained by providing it with images having known correspondence. A 3D model of a city may be utilized in order to train a neural network for location detection. 3D models are sophisticated and allow manipulation of viewer perspective and ambient features such as day/night sky variations, weather variations, and occlusion placement. Various manipulations may be executed in order to generate vast numbers of image pairs having known correspondence despite having variations. These image pairs with known correspondence may be utilized to train the neural network to be able to generate feature maps from query images and identify correspondence between query image feature maps and reference feature maps. This training can be accomplished without requiring the capture of real images with known correspondence. Capture of real images with known correspondence is cumbersome, time and resource-intensive, and difficult to manage.

Claim (Index 2):
The method of  claim 1  further comprising the steps of:\n processing said current image through a feature extractor to obtain a current feature map; \n processing said current feature map through a correspondence matcher against a feature map derived from said neighbor image to obtain a feature extraction correspondence map; \n providing said feature extraction correspondence map as a second training input to said neural network; \n applying a loss function to said feature extraction correspondence map and said ground-truth correspondence map; and \n updating said feature extractor on the basis of a result of the application of said loss function.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 90.0
- Lexical Diversity: 1.95699
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15374010', '15155818', '15138821', '10155948', '15092421']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2670379555010835
- 35 USC 102 Novelty (BERT): 0.4884251098234113
- Combined Prediction Score: 0.2891766709333163
- Mean Citation Score: 162.465678
- Max Citation Score: 169.88301
- Similarity Product: 116.46629040522338

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