Invention Grant
- Patent Title: End to end network model for high resolution image segmentation
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Application No.: US16339122Application Date: 2017-09-27
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Publication No.: US10860919B2Publication Date: 2020-12-08
- Inventor: Noritsugu Kanazawa , Yael Pritch Knaan
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Dority & Manning, P.A.
- International Application: PCT/US2017/053627 WO 20170927
- International Announcement: WO2019/066794 WO 20190404
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06N3/04 ; G06T7/12 ; G06T7/194 ; G06N20/20 ; G06N3/08 ; G06T3/40 ; G06T5/00

Abstract:
The present disclosure provides systems and methods that leverage neural networks for high resolution image segmentation. A computing system can include a processor, a machine-learned image segmentation model comprising a semantic segmentation neural network and an edge refinement neural network, and at least one tangible, non-transitory computer readable medium that stores instructions that cause the processor to perform operations. The operations can include obtaining an image, inputting the image into the semantic segmentation neural network, receiving, as an output of the semantic segmentation neural network, a semantic segmentation mask, inputting at least a portion of the image and at least a portion of the semantic segmentation mask into the edge refinement neural network, and receiving, as an output of the edge refinement neural network, the refined semantic segmentation mask.
Public/Granted literature
- US20200218961A1 End to End Network Model for High Resolution Image Segmentation Public/Granted day:2020-07-09
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