Patent · US Active

Convolutional neural networks for variable prediction using raw data

US11200577B2 · kind B2 · utility

0Cited by

1References

20Claims

0Family size

Assignee

PAYPAL, INC. · US

Inventors

Shiwen Shen · Palo Alto, US
Danielle Zhu · Millbrae, US
Feng Pan · Beijing, CN

Key dates

Filing date	Aug 31, 2017
Grant date	Dec 14, 2021
Priority date	—
Expiry date	Jun 5, 2040

Classification

Technology area (CPC G)Physics
CPC primaryG06Q30/0206
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

While artificial neural networks can be used to predict particular values in certain contexts, convolutional neural networks are not typically used in these contexts—instead they may be employed for image recognition. However, raw transactional data may be structured to take advantage of convolutional neural network (CNN) techniques by arranging the data such that correlations are increased between nearby other data. In arranging data in this manner, the structured CNN (SCNN) can operate efficiently without having to make use of engineered data features, the generation and maintenance of which can be a time-consuming process.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.