Patent · US Active

Transform domain regression convolutional neural network for image segmentation

US10290107B1 · kind B1 · utility

9Cited by

3References

20Claims

0Family size

Assignee

Cadence Design Systems, Inc. · US

Inventors

Raul Alejandro Casas · Doylestown, US
Samer Hijazi · Bethlehem, US
Rishi Kumar · New York, US
Piyush Kaul · New Delhi, IN
Xuehong Mao · San Jose, US
Christopher Rowen · Santa Cruz, US
Himanshu Charaya · Alwar, IN

Key dates

Filing date	Jun 19, 2017
Grant date	May 14, 2019
Priority date	—
Expiry date	Jul 15, 2037

Classification

Technology area (CPC G)Physics
CPC primaryG06T2207/20084
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

Aspects of the present disclosure involve a transform domain regression convolutional neural network for image segmentation. Example embodiments include a system comprising a machine-readable storage medium storing instructions and computer-implemented methods for classifying one or more pixels in an image. The method may include analyzing the image to estimate one or more transform domain coefficients using a multi-layered function such as a convolutional neural network. The method may further include generating a segmented image by applying a change of basis transformation to the estimated one or more transform domain coefficients.

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