PATENT CLAIM ANALYSIS

Application Number: 15880375
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-06
Patent Classification: ["382", "156000"]

Abstract:
Methods and systems for extracting features directly from convolutional layers are disclosed. The last layer in the ordered convolutional layers contains reduced number of channels of features with respect to the immediately prior layer. Filter coefficients of the convolutional layers are trained for image classification task together with fully-connected networks. For image verification task, filter coefficients can be trained using Siamese networks. Training of the filter coefficients is performed in the sequential order of ordered convolutional layers. Once trained, the ordered convolutional layers with the last layer having reduced number of channels can be used directly for extracting features with acceptable accuracy in certain applications (e.g., face verification). Trained filter coefficients can optionally be converted to bi-valued filter coefficients, and then be loaded into a cellular neural networks (CNN) based digital integrated circuit.

Claim (Index 5):
The digital integrated circuit of  claim 3 , wherein the classifier comprises Support Vector Machine.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 86.0
- Lexical Diversity: 1.92208
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15820253', '15709220', '15289726', '15289733', '15861596']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4086227311142107
- 35 USC 102 Novelty (BERT): 0.5367368838865451
- Combined Prediction Score: 0.4214341463914441
- Mean Citation Score: 327.439286
- Max Citation Score: 385.52905
- Similarity Product: 250.1079525636553

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

Dataset: test