Patent · US Active

Image processing using a convolutional neural network

US10706503B2 · kind B2 · utility

2Cited by
3References
20Claims
0Family size

Assignee

Inventors

Key dates

Filing dateMar 13, 2018
Grant dateJul 7, 2020
Priority date
Expiry dateNov 22, 2038

Classification

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

Abstract

According to one implementation, an image processing system includes a computing platform having a hardware processor and a system memory storing a software code including a convolutional neural network (CNN) trained using one or more semantic map(s). The hardware processor executes the software code to receive an original image including multiple object images each identified with one of multiple object classes, and to generate replications of the original image, each replication corresponding respectively to one of the object classes. The hardware processor further executes the software code to, for each replication, selectively modify one or more object image(s) identified with the object class corresponding to the replication, using the CNN, to produce partially modified images each corresponding respectively to an object class, and to merge the partially modified images, using the CNN, to generate a modified image corresponding to the original image.

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