Invention Grant
- Patent Title: Deep machine learning to perform touch motion prediction
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Application No.: US15259917Application Date: 2016-09-08
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Publication No.: US10514799B2Publication Date: 2019-12-24
- Inventor: Pin-chih Lin , Tai-hsu Lin
- Applicant: Google Inc.
- 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.
- Main IPC: G06F3/041
- IPC: G06F3/041 ; G06N20/00 ; G06N3/04 ; G06N3/08 ; G06F3/0488 ; G06F3/0354

Abstract:
The present disclosure provides systems and methods that leverage machine learning to perform user input motion prediction. In particular, the systems and methods of the present disclosure can include and use a machine-learned motion prediction model that is trained to receive motion data indicative of motion of a user input object and, in response to receipt of the motion data, output predicted future locations of the user input object. The user input object can be a finger of a user or a stylus operated by the user. The motion prediction model can include a deep recurrent neural network.
Public/Granted literature
- US20180067605A1 Deep Machine Learning to Perform Touch Motion Prediction Public/Granted day:2018-03-08
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