Invention Grant
- Patent Title: Deep learning coordinate prediction using satellite and service data
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Application No.: US16021317Application Date: 2018-06-28
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Publication No.: US10699398B2Publication Date: 2020-06-30
- Inventor: Chandan Prakash Sheth , Minzhen Yi , Livia Zarnescu Yanez , Sheng Yang , Shivendra Pratap Singh , Alvin AuYoung , Vikram Saxena
- Applicant: Uber Technologies, Inc.
- Applicant Address: US CA San Francisco
- Assignee: Uber Technologies, Inc.
- Current Assignee: Uber Technologies, Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Schwegman Lundberg & Woessner, P.A.
- Main IPC: H04W4/024
- IPC: H04W4/024 ; G06F16/29 ; G06T7/00 ; G06N20/00 ; H04W4/029

Abstract:
Systems and methods of deep learning coordinate prediction using satellite and service data are disclosed herein. In some example embodiments, for each one of a plurality of places, a computer system trains a deep learning model based on training data of the plurality of places. The deep leaning model is configured to generate a predicted geographical location of a place based on satellite image data and service data associated with the place. The training data for each place comprises satellite image data of the place, service data, and a ground truth geographical location of the place. The service data comprises at least one of pick-up data indicating a geographical location at which a provider started transporting a requester in servicing a request associated with the place or drop-off data indicating a geographical location at which the provider completed transporting the requester in servicing the request associated with the place.
Public/Granted literature
- US20190180434A1 DEEP LEARNING COORDINATE PREDICTION USING SATELLITE AND SERVICE DATA Public/Granted day:2019-06-13
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