UTILIZING DEEP LEARNING FOR BOUNDARY-AWARE IMAGE SEGMENTATION

Patent №

US 9,972,092

Granted

2018-05-15

Filed 2016

Owner

ADOBE SYSTEMS INCORPORATED

Lab

AI components

2

ml · vision

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

15086590

Systems and methods are disclosed for segmenting a digital image to identify an object portrayed in the digital image from background pixels in the digital image. In particular, in one or more embodiments, the disclosed systems and methods use a first neural network and a second neural network to generate image information used to generate a segmentation mask that corresponds to the object portrayed in the digital image. Specifically, in one or more embodiments, the disclosed systems and methods optimize a fit between a mask boundary of the segmentation mask to edges of the object portrayed in the digital image to accurately segment the object within the digital image.

Machine learningVisionG06T 7/11G06N 3/045G06N 3/0464G06N 3/08G06N 3/09G06N 7/01G06T 7/12G06T 7/13+5 more

AI classification

Vision1.00
Machine learning1.00
AI hardware0.39
Knowledge representation0.05
Planning0.01
Natural language0.00
Speech0.00
Evolutionary computation0.00

Ownership

ADOBE SYSTEMS INCORPORATED

assignment · 381570841

Assignors

LIN, ZHE, SONG, YIBING, LU, XIN, SHEN, XIAOHUI, YANG, JIMEI

On an employer assignment, the assignors are typically the inventors.

From the same owner

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