Database image matching using machine learning with output estimation
First Claim
1. A system for processing an image including a vehicle using machine learning, comprising:
- a processor in communication with a client device; and
a storage medium storing instructions that, when executed, cause the processor to perform operations comprising;
determining a location of the client device;
mapping the location of the client device to a vehicle dealership;
receiving a first image of a vehicle from an image sensor of the client device;
matching, using machine learning, the first image to one or more images of vehicles in a vehicle database of the vehicle dealership to identify the vehicle, the vehicle database listing vehicles located at the vehicle dealership, the vehicle database including images of the listed vehicles, wherein matching includes;
inputting the image to an input layer of a first convolutional neural network;
extracting features indicating characteristics of the vehicle from an output layer of the first convolutional neural network;
inputting the extracted features to an input layer of a second convolutional neural network;
determining attributes of the vehicle from an output layer of the second convolutional neural network; and
determining the identified vehicle as a vehicle in the matched one or more images in the database having associated attributes matching the determined attributes;
retrieving vehicle information from the vehicle database, based on the identified vehicle;
obtaining comparison information from a comparison resource of a service provider based at least in part on the vehicle information;
estimating a quote for the identified vehicle based on the comparison information; and
transmitting the estimated quote for display on the client device.
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Accused Products
Abstract
A method for processing an image including a vehicle using machine learning can include determining a location of the client device. The method can further include receiving a first image of a vehicle from an image sensor of the client device and matching, using machine learning, the first image to one or more images of vehicles in a vehicle database to identify the vehicle. The vehicle database can list vehicles located at the determined location of the client device and images of the vehicles. The method can include retrieving vehicle information from the vehicle database, based on the identified vehicle, and obtaining comparison information based at least in part on the vehicle information. The method can include estimating a quote for the vehicle based on the comparison information and transmitting the estimated quote for display on the client device.
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Citations
17 Claims
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1. A system for processing an image including a vehicle using machine learning, comprising:
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a processor in communication with a client device; and a storage medium storing instructions that, when executed, cause the processor to perform operations comprising; determining a location of the client device; mapping the location of the client device to a vehicle dealership; receiving a first image of a vehicle from an image sensor of the client device; matching, using machine learning, the first image to one or more images of vehicles in a vehicle database of the vehicle dealership to identify the vehicle, the vehicle database listing vehicles located at the vehicle dealership, the vehicle database including images of the listed vehicles, wherein matching includes; inputting the image to an input layer of a first convolutional neural network; extracting features indicating characteristics of the vehicle from an output layer of the first convolutional neural network; inputting the extracted features to an input layer of a second convolutional neural network; determining attributes of the vehicle from an output layer of the second convolutional neural network; and determining the identified vehicle as a vehicle in the matched one or more images in the database having associated attributes matching the determined attributes; retrieving vehicle information from the vehicle database, based on the identified vehicle; obtaining comparison information from a comparison resource of a service provider based at least in part on the vehicle information; estimating a quote for the identified vehicle based on the comparison information; and transmitting the estimated quote for display on the client device. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A computer-implemented method for processing an image including a vehicle using machine learning, the method comprising:
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determining a location of a client device; mapping the location of the client device to a vehicle dealership; receiving a first image of a vehicle from an image sensor of the client device; matching, by a system using machine learning, the first image to one or more images of vehicles in a vehicle database of the vehicle dealership to identify the vehicle, the vehicle database listing vehicles located at the vehicle dealership, the vehicle database including images of the listed vehicles, wherein matching includes; inputting the image to an input layer of a first convolutional neural network; extracting features indicating characteristics of the vehicle from an output layer of the first convolutional neural network; inputting the extracted features to an input layer of a second convolutional neural network; determining attributes of the vehicle from an output layer of the second convolutional neural network; and determining the identified vehicle as a vehicle in the matched one or more images in the database having associated attributes matching the determined attributes; retrieving vehicle information from the vehicle database, based on the identified vehicle; obtaining comparison information from a comparison resource of a service provider based at least in part on the vehicle information; estimating a quote for the identified vehicle based on the comparison information; and transmitting the estimated quote for display on the client device. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15)
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16. A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the processor to operate a computer system for processing an image including a vehicle using machine learning, comprising:
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determining a location of a client device; mapping the location of the client device to a vehicle dealership; receiving a first image of a vehicle from an image sensor of the client device; matching, using machine learning, the first image to one or more images of vehicles in a vehicle database of the vehicle dealership to identify the vehicle, the vehicle database listing vehicles located at the vehicle dealership, the vehicle database including images of the listed vehicles, wherein matching includes; inputting the image to an input layer of a first convolutional neural network; extracting features indicating characteristics of the vehicle from an output layer of the first convolutional neural network; inputting the extracted features to an input layer of a second convolutional neural network; determining attributes of the vehicle from an output layer of the second convolutional neural network; and determining the identified vehicle as a vehicle in the matched one or more images in the database having associated attributes matching the determined attributes retrieving vehicle information from the vehicle database, based on the identified vehicle; obtaining comparison information from a comparison resource of a service provider based at least in part on the vehicle information; estimating a quote for the identified vehicle based on the comparison information; and transmitting the estimated quote for display on the client device. - View Dependent Claims (17)
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Specification