Abstract: A system, process, and computer-readable medium for securely transferring user personal identification information (PII) across platforms, based on specific permissions, are described. One or more aspects provide greater control, to a user, of when that user's PII may be released from a secure storage in a first platform and securely provided to a second platform. The timing of those releases of the PII may be controlled by specific authorizations from the user via one or more processes. Also, in addition to improving the security associated with the PII transferred between platforms, one or more aspects improve users' experiences by permitting controlled reuse of users' PII to simplify how users provide their PII to separate processes being performed on separate platforms.

Abstract: A computer-implemented method for providing a vehicle recommendation to a user may include: obtaining one or more vehicle images via a device associated with the user; identifying one or more user-selected images of the one or more vehicle images based on user interaction with the one or more vehicle images performed by the user via a user interface; identifying one or more first-level attributes from the one or more user-selected images; obtaining one or more vehicle identifications from the one or more user-selected images; determining one or more second-level attributes based on the one or more vehicle identifications; determining a value of each of the one or more first-level attributes and the one or more second-level attributes; determining the vehicle recommendation based on the value; and transmitting, to the device associated with the user, a notification indicating the vehicle recommendation.

Abstract: A system, process, and computer-readable medium for securely transferring user personal identification information (PII) across platforms, based on specific permissions, are described. One or more aspects provide greater control, to a user, of when that user's PII may be released from a secure storage in a first platform and securely provided to a second platform. The timing of those releases of the PII may be controlled by specific authorizations from the user via one or more processes. Also, in addition to improving the security associated with the PII transferred between platforms, one or more aspects improve users' experiences by permitting controlled reuse of users' PII to simplify how users provide their PII to separate processes being performed on separate platforms.

Abstract: A system, process, and computer-readable medium for securely transferring user personal identification information (PII) across platforms, based on specific permissions, are described. One or more aspects provide greater control, to a user, of when that user's PII may be released from a secure storage in a first platform and securely provided to a second platform. The timing of those releases of the PII may be controlled by specific authorizations from the user via one or more processes. Also, in addition to improving the security associated with the PII transferred between platforms, one or more aspects improve users' experiences by permitting controlled reuse of users' PII to simplify how users provide their PII to separate processes being performed on separate platforms.

Abstract: Computer-implemented methods and systems include determining vehicle grades for a user by accessing a plurality of user platforms, identifying user-related content linked to the user via the user platforms, extracting user attributes based on the user-related content, applying weights to vehicle attributes in a vehicle recommendation engine, based on the extracted user attributes, generating the vehicle grades based on the weights, and providing the vehicle grades to the user via a vehicle grading platform.

Abstract: Disclosed are examples related to building a customized data collection widget. Building of the customized data collection widget includes receiving a selection of several universal modules for inclusion in the widget. Each universal module of the selected several universal modules may include programming code that causes rendering of user-fillable data fields on a display, and a summary page including data requirements of the respective universal module. Based on the data requirements in a summary page of each respective universal module of the selected several universal modules, the selected several universal modules retrieved from a module repository may be combined in a customized data collection container stored in a composite repository. The selected customized data collection container may be combined with selected other data collection containers to form a uniquely identifiable, customized data collection widget. The customized data collection widget may be delivered to the composite repository.

Abstract: Computer-implemented methods and systems include determining vehicle grades for a user by accessing a plurality of user platforms, identifying user-related content linked to the user via the user platforms, extracting user attributes based on the user-related content, applying weights to vehicle attributes in a vehicle recommendation engine, based on the extracted user attributes, generating the vehicle grades based on the weights, and providing the vehicle grades to the user via a vehicle grading platform.

Abstract: A weakly paired image style transfer method based on a pose self-supervised generative adversarial network, relating to the field of image processing. The method is suitable for style transfer of weakly paired images, different styles of pictures having certain overlap are used to perform model training of an adversarial neural network, so that the model is insensitive to poses and focuses on style learning, and therefore, in an actual application process, a source style can be converted into a target style, but a pose is kept unchanged. In addition, in the model training process of the adversarial neural network, a differentiable pose solver capable of estimating a relative pose of any two images is introduced, a phase correlation algorithm is optimized to be differentiable, and the phase correlation algorithm is embedded into an end-to-end learning network framework to achieve pose estimation.

Abstract: Disclosed are examples related to building a customized data collection widget. Building of the customized data collection widget includes receiving a selection of several universal modules for inclusion in the widget. Each universal module of the selected several universal modules may include programming code that causes rendering of user-fillable data fields on a display, and a summary page including data requirements of the respective universal module. Based on the data requirements in a summary page of each respective universal module of the selected several universal modules, the selected several universal modules retrieved from a module repository may be combined in a customized data collection container stored in a composite repository. The selected customized data collection container may be combined with selected other data collection containers to form a uniquely identifiable, customized data collection widget. The customized data collection widget may be delivered to the composite repository.

Abstract: A system, process, and computer-readable medium for securely transferring user personal identification information (PII) across platforms, based on specific permissions, are described. One or more aspects provide greater control, to a user, of when that user's PII may be released from a secure storage in a first platform and securely provided to a second platform. The timing of those releases of the PII may be controlled by specific authorizations from the user via one or more processes. Also, in addition to improving the security associated with the PII transferred between platforms, one or more aspects improve users' experiences by permitting controlled reuse of users' PII to simplify how users provide their PII to separate processes being performed on separate platforms.

Abstract: A system, process, and computer-readable medium for securely transferring user personal identification information (PII) across platforms, based on specific permissions, are described. One or more aspects provide greater control, to a user, of when that user's PII may be released from a secure storage in a first platform and securely provided to a second platform. The timing of those releases of the PII may be controlled by specific authorizations from the user via one or more processes. Also, in addition to improving the security associated with the PII transferred between platforms, one or more aspects improve users' experiences by permitting controlled reuse of users' PII to simplify how users provide their PII to separate processes being performed on separate platforms.

Abstract: A computer-implemented method of generating a graphic for a vehicle item may include: causing a user device to display a user interface indicative of one or more vehicles; receiving, from the user device, vehicle selection information, the vehicle selection information indicative of a vehicle selected by a user; obtaining, from a database, user data corresponding to the user; generating, using a machine learning model, a first score corresponding to a first vehicle item based on the user data; determining whether the first score exceeds a first predetermined score threshold; generating, in response to a determination that the first score exceeds the first predetermined score threshold, a first graphic indicative of the first vehicle item; and causing the user device to display the first graphic via the user interface.

Abstract: Methods and systems are disclosed for providing a vehicle suggestion to a user based on image analysis. The method may include: receiving one or more vehicle images via website data associated with the user; identifying one or more first-level traits from the one or more vehicle images; obtaining one or more vehicle identifications from the one or more vehicle images based on the one or more first-level traits; determining a value of each of the one or more first-level traits and/or the one or more vehicle identifications via one or more algorithms; determining the vehicle suggestion based on the value of each of the one or more first-level traits and/or the one or more vehicle identifications; and transmitting, to a device associated with the user, a notification indicating the vehicle suggestion.

Abstract: A computer-implemented method for providing a vehicle recommendation to a user may include: obtaining one or more vehicle images via a device associated with the user; identifying one or more user-selected images of the one or more vehicle images based on user interaction with the one or more vehicle images performed by the user via a user interface; identifying one or more first-level attributes from the one or more user-selected images; obtaining one or more vehicle identifications from the one or more user-selected images; determining one or more second-level attributes based on the one or more vehicle identifications; determining a value of each of the one or more first-level attributes and the one or more second-level attributes; determining the vehicle recommendation based on the value; and transmitting, to the device associated with the user, a notification indicating the vehicle recommendation.

Abstract: A computer-implemented method for providing a vehicle recommendation to a user may include: obtaining one or more vehicle images via a device associated with the user; identifying one or more user-selected images of the one or more vehicle images based on user interaction with the one or more vehicle images performed by the user via a user interface; identifying one or more first-level attributes from the one or more user-selected images; obtaining one or more vehicle identifications from the one or more user-selected images; determining one or more second-level attributes based on the one or more vehicle identifications; determining a value of each of the one or more first-level attributes and the one or more second-level attributes; determining the vehicle recommendation based on the value; and transmitting, to the device associated with the user, a notification indicating the vehicle recommendation.

Abstract: Methods and systems are disclosed for providing a vehicle suggestion to a user based on image analysis. The method may include: receiving one or more vehicle images via website data associated with the user; identifying one or more first-level traits from the one or more vehicle images; obtaining one or more vehicle identifications from the one or more vehicle images based on the one or more first-level traits; determining a value of each of the one or more first-level traits and/or the one or more vehicle identifications via one or more algorithms; determining the vehicle suggestion based on the value of each of the one or more first-level traits and/or the one or more vehicle identifications; and transmitting, to a device associated with the user, a notification indicating the vehicle suggestion.

Abstract: Computer-implemented methods and systems include determining vehicle grades for a user by accessing a plurality of user platforms, identifying user-related content linked to the user via the user platforms, extracting user attributes based on the user-related content, applying weights to vehicle attributes in a vehicle recommendation engine, based on the extracted user attributes, generating the vehicle grades based on the weights, and providing the vehicle grades to the user via a vehicle grading platform.

Abstract: Methods and systems are disclosed for providing a vehicle suggestion to a user based on image analysis. The method may include: receiving one or more vehicle images via website data associated with the user; identifying one or more first-level traits from the one or more vehicle images; obtaining one or more vehicle identifications from the one or more vehicle images based on the one or more first-level traits; determining a value of each of the one or more first-level traits and/or the one or more vehicle identifications via one or more algorithms; determining the vehicle suggestion based on the value of each of the one or more first-level traits and/or the one or more vehicle identifications; and transmitting, to a device associated with the user, a notification indicating the vehicle suggestion.

Abstract: A computer-implemented method for providing a vehicle recommendation to a user may include: obtaining one or more vehicle images via a device associated with the user; identifying one or more user-selected images of the one or more vehicle images based on user interaction with the one or more vehicle images performed by the user via a user interface; identifying one or more first-level attributes from the one or more user-selected images; obtaining one or more vehicle identifications from the one or more user-selected images; determining one or more second-level attributes based on the one or more vehicle identifications; determining a value of each of the one or more first-level attributes and the one or more second-level attributes; determining the vehicle recommendation based on the value; and transmitting, to the device associated with the user, a notification indicating the vehicle recommendation.

Abstract: Disclosed are examples related to building a customized data collection widget. Building of the customized data collection widget includes receiving a selection of several universal modules for inclusion in the widget. Each universal module of the selected several universal modules may include programming code that causes rendering of user-fillable data fields on a display, and a summary page including data requirements of the respective universal module. Based on the data requirements in a summary page of each respective universal module of the selected several universal modules, the selected several universal modules retrieved from a module repository may be combined in a customized data collection container stored in a composite repository. The selected customized data collection container may be combined with selected other data collection containers to form a uniquely identifiable, customized data collection widget. The customized data collection widget may be delivered to the composite repository.