DEEP LEARNING COORDINATE PREDICTION USING SATELLITE AND SERVICE DATA

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 mod...

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Bibliographische Detailangaben
Hauptverfasser:	Singh, Shivendra Pratap, Yi, Minzhen, Yanez, Livia Zarnescu, Sheth, Chandan Prakash, Saxena, Vikram, Yang, Sheng, AuYoung, Alvin
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTING COUNTING ELECTRIC COMMUNICATION TECHNIQUE ELECTRICITY IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS WIRELESS COMMUNICATIONS NETWORKS
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Beschreibung
Zusammenfassung:	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.