Database image matching using machine learning with output personalization

A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to operate a client device for processing an image including a vehicle using machine learning, comprising:

• determining a location of the client device;
• capturing an image of a vehicle using a sensor of the client device;
• matching, using a machine learning algorithm, the image to one or more images of vehicles in a database, the database listing vehicles located at the determined location, the database including images of the vehicles, wherein the
• matching comprises:
• 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 network;
• and
• identifying the matched one or more images in the database as images having associated attributes matching the determined attributes;
• retrieving vehicle information from the database based on the matched one or more images in the database;
• obtaining user information relating to a financing request for the vehicle;
• determining a real-time purchase quote for the vehicle based on the vehicle information and the user information;
• and
• displaying the real-time purchase quote on a display of the client device.

A computer-implemented method for processing an image including a vehicle using machine learning, the method comprising the following operations performed by at least one processor of a client device:

• capturing an image of a vehicle using a sensor of the client device;
• matching, using a machine learning algorithm, the image to one or more images of vehicles in a database, the database including images of the vehicles, wherein the matching comprises:
• 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 network;
• and
• identifying the matched one or more images in the database as images having associated attributes matching the determined attributes;
• retrieving vehicle information from the database based on the matched one or more images in the database;
• displaying a prompt for authentication information on the display;
• receiving, in response to the prompt, authentication information associated with a user;
• accessing user information using the received authentication information;
• determining a real-time purchase quote for the vehicle based on the vehicle information and the user information;
• and
• displaying the real-time purchase quote on a display of the client device, a display of the client device.