US 12,073,442 B2
Systems and methods for automated trade-in with limited human interaction
Micah Price, The Colony, TX (US); Avid Ghamsari, Carrollton, TX (US); Geoffrey Dagley, McKinney, TX (US); Qiaochu Tang, Frisco, TX (US); and Jason Hoover, Grapevine, TX (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Oct. 26, 2022, as Appl. No. 17/974,104.
Application 17/974,104 is a continuation of application No. 16/934,295, filed on Jul. 21, 2020, granted, now 11,514,483.
Application 16/934,295 is a continuation of application No. 16/659,809, filed on Oct. 22, 2019, granted, now 10,762,540, issued on Sep. 1, 2020.
Prior Publication US 2023/0065825 A1, Mar. 2, 2023
Int. Cl. G06N 20/00 (2019.01); G06F 18/24 (2023.01); G06Q 30/02 (2023.01); G06Q 30/0201 (2023.01); G06T 7/00 (2017.01); G06T 7/70 (2017.01); G06V 10/40 (2022.01); G06V 10/46 (2022.01); G06V 10/764 (2022.01); G06V 20/00 (2022.01)
CPC G06Q 30/0278 (2013.01) [G06F 18/24 (2023.01); G06N 20/00 (2019.01); G06Q 30/0206 (2013.01); G06T 7/70 (2017.01); G06T 7/97 (2017.01); G06V 10/40 (2022.01); G06V 10/462 (2022.01); G06V 10/764 (2022.01); G06V 20/00 (2022.01); G06T 2207/10016 (2013.01); G06T 2207/30248 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving a first indication that a use period of a vehicle associated with a user has started;
receiving, based on the first indication, preliminary data for the vehicle associated with the user;
receiving, from a device associated with the user, a second indication that the use period has ended;
receiving, in response to the second indication and from one or more image sensors, first data comprising:
vehicle-specific identifying information of the vehicle, and
multimedia content showing a first aspect of the vehicle;
creating a feature vector comprising the first data;
inputting the feature vector into a machine learning algorithm corresponding to the vehicle-specific identifying information of the vehicle associated with the user;
determining, using the machine learning algorithm, an instance of damage to the vehicle associated with the user based on the first data and the preliminary data; and
sending, to a mobile device associated with the user, an indication of the instance of damage to the vehicle associated with the user.