PATENT CLAIM ANALYSIS

Application Number: 15894867
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-07
Patent Classification: ["382", "157000"]

Abstract:
Tasks such as object classification from image data can take advantage of a deep learning process using convolutional neural networks. These networks can include a convolutional layer followed by an activation layer, or activation unit, among other potential layers. Improved accuracy can be obtained by using a generalized linear unit (GLU) as an activation unit in such a network, where a GLU is linear for both positive and negative inputs, and is defined by a positive slope, a negative slope, and a bias. These parameters can be learned for each channel or a block of channels, and stacking those types of activation units can further improve accuracy.

Claim (Index 2):
A computer-implemented method, comprising:\n receiving a query from a client device associated with a user; processing the query using a trained convolutional neural network to determine a classification of a data object represented in the query, the trained convolutional neural network containing at least one convolutional layer and at least one activation layer, the at least one activation layer including a generalized linear unit, the generalized linear unit having a functional form described using a pair of straight lines with three parameters including a first slope in a positive region, a second slope in a negative region, and an offset applied to the first slope and the second slope; determining a set of features corresponding to the classification; and providing, to the client device, information for at least a subset of the set of features

Metadata:
- Claim Count in Document: 3.0
- Percentile: 88.0
- Lexical Diversity: 1.73913
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14954646', '15802585', '10837382', '15352821', '15551870']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3036597150875489
- 35 USC 102 Novelty (BERT): 0.5121393524021898
- Combined Prediction Score: 0.3245076788190131
- Mean Citation Score: 177.93588400000004
- Max Citation Score: 313.96484
- Similarity Product: 263.2257658980656

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

Dataset: test