Abstract: Disclosed embodiments provide systems, methods, and computer-readable storage media for stress testing a vehicle identification model by determining image quality parameters optimizing model confidence values. The embodiments comprise one or more memory devices storing instructions and one or more processors configured to execute instructions. The one or more processors perform operations comprising receiving a first set of images of the vehicle, wherein the images contain preset values for parameters comprising at least one of a rotation, a focus, a contrast, and a color. The system further analyzes the first set of images with an identification model and determining an initial identification confidence of the vehicle. The system further modifies the first set of images, compares the modified images to the first set of images, and determines whether the model should be modified based on at least the comparison.

Abstract: A system for inspecting the reliability of an image. The system may include a processor in communication with a client device; and a storage medium. The storage medium may store instructions that, when executed, configure the processor to perform operations including: obtaining a plurality of images; categorizing the images into a plurality of image classes; calculating a plurality of probability outcomes; determining whether highest predicted probabilities of the images are less than a first threshold and whether an entropy of a predicted density of the probability outcomes exceeds a second threshold; indicating whether the image is associated with the image classes; ranking, the image amongst the plurality of images; filtering, a plurality of low reliability images according to a third threshold; providing, a likelihood of whether a user scanned a vehicle object associated with the image; and identifying a percentage of user scan failures.

Abstract: A system for generating graphical user interfaces. The system may include processors and storage devices storing instructions. The instructions may configure the one or more processors to perform operations including identifying a plurality of attributes from an image captured with a client device, identifying a plurality of first results based on the attributes, generating a first graphical user interface for display in the client device. The first graphical user interface may include a plurality of result icons corresponding to a subset of the first results having confidence scores above a threshold, a plurality of filter icons displaying options, and a search button. The operations may also include receiving a selection of at least one of the result icons or at least one of the filter icons, performing a search, based on the selection, and generating a second graphical user interface.

Abstract: Disclosed embodiments provide systems, methods, and computer-readable storage media for enhancing a vehicle identification with preprocessing. The system may comprise memory and processor devices to execute instructions for receiving an image depicting a vehicle. The image may be analyzed and first predicted identity and first confidence value may be determined. The first confidence value may be compared to a predetermined threshold. The processors may further select a processing technique for modifying the image and further analyze the modified image determining a second predicted identity of the vehicle. And a second confidence value may be determined. And the system may further compare the second confidence value to the predetermined threshold to select the first or second predicted identity for transmission to a user.

Abstract: The present disclosure relates to systems and methods for training image recognition models. The system may include a processor in communication with a client device, and a storage medium storing instructions that, when executed, cause the processor to perform operations including storing, in a database, a plurality of images depicting vehicles; determining, for a first subset of the images, that additional images of the vehicles depicted in the first subset are desired; determining, for a second subset of the images, that additional images of the vehicles depicted in the second subset are not desired; identifying, within the first subset, images suitable for training an image recognition model; assigning a classification to the suitable images; determining, based on the classification, whether a threshold number of images exist in the database; and initiating an update of the image recognition model, based on the determination of whether the threshold number of images exists.

Abstract: Disclosed embodiments provide systems, methods, and computer-readable storage media for stress testing a vehicle identification model by determining image quality parameters optimizing model confidence values. The embodiments comprise one or more memory devices storing instructions and one or more processors configured to execute instructions. The one or more processors perform operations comprising receiving a first set of images of the vehicle, wherein the images contain preset values for parameters comprising at least one of a rotation, a focus, a contrast, and a color. The system further analyzes the first set of images with an identification model and determining an initial identification confidence of the vehicle. The system further modifies the first set of images, compares the modified images to the first set of images, and determines whether the model should be modified based on at least the comparison.