Abstract: A computer-implemented method for processing images may include obtaining at least one image for analyzing; inputting the at least one image to at least one of a plurality of image plugins; analyzing the at least one image via the at least one of the plurality of image plugins; determining metadata related to the at least one image based on the at least one of the plurality of image plugins; filtering the at least one image based on one or more rule sets to generate at least one filtered image; sorting the at least one filtered image to generate at least one sorted image; displaying the at least one sorted image based on an organizational sequence of a webpage; displaying navigation controls via the webpage; and displaying the at least one sorted image according to a user interaction with the navigation controls on the webpage.

Abstract: According to certain aspects of the disclosure, a computer-implemented method may be used for determining one or more vehicle recommendations. The method may include receiving data pertaining to a user's internet browsing activity. The received data may be indicative of the user's automotive vehicle preferences. The method may include comparing the received data to a collection of stored vehicle qualities. The method also may include identifying, based on the received data and the comparison of the received data to the collection of stored vehicle qualities, a vehicle characteristic of interest to the user. Using the vehicle characteristic of interest, one or more vehicle recommendations may be determined. One or more vehicle recommendations may be communicated to the user.

Abstract: A chatbot in the context of a chat group messaging is described. The chat group can include a plurality of users and a chatbot. A set of rules can be defined for the users of the group granting each user a privilege status. The chatbot can receive a request through a message transmitted to the chat group. The chatbot can discern a task associated with the message, and perform the task or ask another module to perform the task. Once the task is performed, the chatbot can report the results to the chat group. The chatbot can include a conflict resolution module which can resolve conflicts. The conflict resolution module can use each user's privilege status to resolve the conflicts.

Abstract: Systems and methods for providing a disposal recommendation for a vehicle are provided. The method includes generating a profile for a first vehicle, the first vehicle being an income generating vehicle and the first vehicle profile including at least age, mileage, and location of the first vehicle, receiving monitoring data of the first vehicle, and receiving sales data for second vehicles, the second vehicles corresponding to the profile. The method may further include generating predicted depreciation data of the first vehicle, based on the sales data and the monitoring data, generating a predicted profit data from the first vehicle, and providing a recommended disposal time for the first vehicle, based on the predicted depreciation data and the predicted profit data.

Abstract: A device may determine that a user device, associated with a user, and a first object for comparison are within a threshold proximity of one another. The device may communicate with the user device to obtain a comparison profile, associated with the user, based on determining that the user device and the first object are within the threshold proximity of one another. The device may identify, based on the comparison profile, a set of desired attributes. The device may identify, based on the comparison profile, a set of attribute categories to be used to compare the first object and the set of desired attributes. The device may determine a first set of attributes of the first object for the set of attribute categories. The device may present, for display, information that identifies one or more attributes of the first set of attributes or the set of desired attributes.

Abstract: Systems and methods for providing a disposal recommendation for an owned vehicle are provided. The method includes generating a profile for the owned vehicle, the profile including age, mileage, and location of the owned vehicle, receiving monitoring data of the owned vehicle, and receiving sales data for non-owned vehicles corresponding to the profile. The method may further include generating predicted depreciation data of the owned vehicle, based on the sales data and the monitoring data, and providing a recommended disposal time for the owned vehicle, based on the predicted depreciation data.

Abstract: A smart device is provided with an application program for displaying a video feed received from the smart device's camera. The application can determine the coordinates for an intersection point, which is a point on the ground where the smart device is pointing at. The application can display a target on the visual representation of the intersection point. Based on whether the smart device is at an appropriate distance from the intersection point, the user interface can superimpose an indicator on the video feed received from the camera. This can inform the user whether the smart device is at an optimal scan distance from the intersection point (or an object) so that the object can be identified by a machine learning model.

Abstract: A device including a storage medium storing instructions, and at least one processor configured to execute the stored instructions to perform operations is provided. The operations include displaying on a display screen an interactive scene containing an augmented reality element, receiving input to change display of the interactive scene, and receiving a request to simulate the capturing of image data representing the interactive scene. The operations further include determining a position of the augmented reality element relative to a region defined on the display screen, simulating the capturing of the image data representing the interactive scene, and providing, based on the determined position, an indication of whether the simulation has succeeded.

Abstract: Various embodiments are generally directed to techniques of overlaying a virtual object on a physical object in augmented reality (AR). A computing device may receive one or more images of the physical object, perform analysis on the images (such as image segmentation) to generate a digital outline, and determine a position and a scale of the physical object based at least in part on the digital outline. The computing device may configure (e.g., rotate, scale) a 3D model of the physical object to match the determined position and scale of the physical object. The computing device may place or overlay a 3D virtual object on the physical object in AR based on a predefined location relation between the 3D virtual object and the 3D model of the physical object, and further, generate a composite view of the placement or overlay.

Abstract: A device receives image data of a contractual document that includes an offer including terms of a proposed transaction, converts the image data to text data that identifies text within the contractual document, and receives preferences information for a recipient of the offer. The device identifies key terms within the contractual document by using term identification to analyze the text. The key terms may include a first key term that identifies subject matter of the proposed transaction and other key terms that are part of the offer. The device determines term scores that correspond to likelihoods of the other key terms being favorable to the recipient by using a data model to analyze the key terms and the preferences information. The device, based on the term scores, generates and provides another device with a recommendation to be used in determining whether the accept the offer.

Abstract: The present disclosure provides systems and methods for creating and updating vehicle listings using crowdsourced images. An exemplary embodiment of the disclosed systems and methods includes at least one processor and at least one non-transitory computer-readable medium containing instructions. The instructions, when executed by the at least one processor, cause the system to perform operations. The operations include communicating with a listing system to create a listing for a vehicle and receiving, from an identification application executing on a mobile device distinct from the listing system, an identifier for the vehicle and an image of the vehicle. The operations further include identifying the listing using the received identifier, determining one or more parameters associated with an image quality for the received image, and updating the listing for the vehicle to include the received image based on the determined one or more parameters for the received image.

Abstract: Systems and methods for providing a disposal recommendation for an owned vehicle are provided. The method includes generating a profile for the owned vehicle, the profile including age, mileage, and location of the owned vehicle, receiving monitoring data of the owned vehicle, and receiving sales data for non-owned vehicles corresponding to the profile. The method may further include generating predicted depreciation data of the owned vehicle, based on the sales data and the monitoring data, and providing a recommended disposal time for the owned vehicle, based on the predicted depreciation data.

Abstract: A smart device is provided with an application program for displaying a video feed received from the smart device's camera. The application can determine the coordinates for an intersection point, which is a point on the ground where the smart device is pointing at. The application can display a target on the visual representation of the intersection point. Based on whether the smart device is at an appropriate distance from the intersection point, the user interface can superimpose an indicator on the video feed received from the camera. This can inform the user whether the smart device is at an optimal scan distance from the intersection point (or an object) so that the object can be identified by a machine learning model.

Abstract: A smart device is provided with an application program for displaying a video feed received from the smart device's camera. The application can determine the coordinates for an intersection point, which is a point on the ground where the smart device is pointing at. The application can display a target on the visual representation of the intersection point. Based on whether the smart device is at an appropriate distance from the intersection point, the user interface can superimpose an indicator on the video feed received from the camera. This can inform the user whether the smart device is at an optimal scan distance from the intersection point (or an object) so that the object can be identified by a machine learning model.

Abstract: Systems and methods are disclosed for providing purchase recommendations. According to some examples, a method may include: determining a set of vehicle characteristics represented in a candidate set of vehicles; for each vehicle characteristic in the set of vehicle characteristics, determining a percentage of the candidate set possessing the respective vehicle characteristic; selecting, from the set of vehicle characteristics, a vehicle characteristic based on a proximity of the respectively determined percentage to 50%; transmitting, to a user device associated with a user, an inquiry for a user preference regarding the selected vehicle characteristic; receiving, from the user device, a response indicating the user preference regarding the selected vehicle characteristic; excluding vehicles from the candidate set based on the indicated user preference to obtain a reduced candidate set; and transmitting, to the user device, a recommendation of one or more vehicles from the reduced candidate set.

Abstract: A smart device is provided with an application program for displaying a video feed received from the smart device's camera. The application can determine the coordinates for an intersection point, which is a point on the ground where the smart device is pointing at. The application can display a target on the visual representation of the intersection point. Based on whether the smart device is at an appropriate distance from the intersection point, the user interface can superimpose an indicator on the video feed received from the camera. This can inform the user whether the smart device is at an optimal scan distance from the intersection point (or an object) so that the object can be identified by a machine learning model.

Abstract: A smart device is provided with an application program for displaying a video feed received from the smart device's camera. The application can determine the coordinates for an intersection point, which is a point on the ground where the smart device is pointing at. The application can display a target on the visual representation of the intersection point. Based on whether the smart device is at an appropriate distance from the intersection point, the user interface can superimpose an indicator on the video feed received from the camera. This can inform the user whether the smart device is at an optimal scan distance from the intersection point (or an object) so that the object can be identified by a machine learning model.