PATENT CLAIM ANALYSIS

Application Number: 15751325
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2019-08
Patent Classification: ["382", "157000"]

Abstract:
According to the embodiments of the present disclosure, there is provided a method for detecting feature points in an image. The method comprises: processing data of the image using a first type of convolutional layers in a Convolutional Neural Network (CNN) to generate first processed data, wherein the first type of convolutional layers comprise convolution kernels having non-shared weights; processing the first processed data using a second type of convolutional layers in the CNN to generate second processed data, wherein the second type of convolutional layers comprise convolution kernels having shared weights; and determining the feature points in the image based on the second processed data. In addition, the embodiments of the present disclosure further provide a corresponding device and a corresponding computer readable storage medium.

Claim (Index 11):
The method according to  claim 1 , wherein the CNN is trained using a Stochastic Gradient Descent (SGD) method.

Metadata:
- Claim Count in Document: 7.0
- Percentile: 88.0
- Lexical Diversity: 2.19048
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['15719829', '15487091', '14609775', '15712654', '15879732']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3516607694672197
- 35 USC 102 Novelty (BERT): 0.5147942389394821
- Combined Prediction Score: 0.3679741164144459
- Mean Citation Score: 251.559726
- Max Citation Score: 257.3886
- Similarity Product: 149.07819598960876

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 0

Dataset: test