Abstract: Systems, devices, and techniques are disclosed for a synchronous virtual classrooms using artificial intelligence techniques. Meeting data from a virtual meeting client connected to a virtual meeting through a virtual meeting server may be received at a virtual AI avatar. The virtual AI avatar may send the meeting data to an AI agent. Avatar action data generated by the AI agent based on a portion of the meeting data may be received at the virtual AI avatar, from the AI agent. Virtual AI avatar data may be generated based on the avatar action data. The virtual AI avatar data may include generated video data, generated audio data, text data, or data causing interactions with a virtual meeting client interface of the virtual meeting client. The virtual AI avatar data may be sent to the virtual meeting client.

Abstract: An illustrative computing system generates, based on a plurality of point-of-interest data records each including data representative of a distinct set of features for a distinct point-of-interest associated with a distinct geographic location, a graph data structure that includes the plurality of point-of-interest data records and a plurality of weighted feature relationships interconnecting the plurality of point-of-interest data records. The computing system generates one or more merged point-of-interest data records based on the graph data structure and provides the one or more merged point-of-interest data records to a mapping system to indicate one or more points-of-interest on a user interface map of a geographic area.

Abstract: An illustrative computing system generates, based on a plurality of point-of-interest data records each including data representative of a distinct set of features for a distinct point-of-interest associated with a distinct geographic location, a graph data structure that includes the plurality of point-of-interest data records and a plurality of weighted feature relationships interconnecting the plurality of point-of-interest data records. The computing system generates one or more merged point-of-interest data records based on the graph data structure and provides the one or more merged point-of-interest data records to a mapping system to indicate one or more points-of-interest on a user interface map of a geographic area.

Abstract: An exemplary point-of-interest merging system accesses point-of-interest data records. Each point-of-interest data record includes data representative of a distinct set of features for a distinct point-of-interest. The merging system generates, based on the distinct sets of features of the point-of-interest data records, a graph data structure that includes the point-of-interest data records and weighted feature relationships interconnecting the point-of-interest data records. The merging system clusters, based on the graph data structure, the point-of-interest data records into subset groups of point-of-interest data records. The merging system generates one or more merged point-of-interest data records based on the clustered subset groups of point-of-interest data records.

Abstract: An exemplary geospatial image processing system generates, based on multiple detections of an object of interest detected by a computer vision model in multiple, correlated images of a geospatial location captured from different camera viewpoints, user interface content that includes a visual indication of the detected object of interest superimposed at an object position on a view of the geospatial location. The system provides the user interface content for display in a graphical user interface view of a user interface and provides, by way of the user interface, a user interface tool configured to facilitate user validation of one or more of the multiple detections of the object of interest. The system may receive, a user validation of one or more of the multiple detections of the object of interest and may train the computer vision model based on the user validation. Corresponding methods and systems are also disclosed.

Abstract: Exemplary systems and methods perform post-processing operations on computer vision model detections of objects of interest in geospatial imagery to detect and assign attributes to the detected objects of interest. For example, an exemplary post-processing system correlates multiple detections, made by a computer vision model, of an object of interest depicted within a set of images of a geospatial location, determines, based on the correlated detections, an attribute of the object of interest depicted within the set of images of the geospatial location, and selects the attribute for inclusion in a dataset for the object of interest. Corresponding methods and systems are also disclosed.

Abstract: An exemplary point-of-interest merging system accesses point-of-interest data records. Each point-of-interest data record includes data representative of a distinct set of features for a distinct point-of-interest. The merging system generates, based on the distinct sets of features of the point-of-interest data records, a graph data structure that includes the point-of-interest data records and weighted feature relationships interconnecting the point-of-interest data records. The merging system clusters, based on the graph data structure, the point-of-interest data records into subset groups of point-of-interest data records. The merging system generates one or more merged point-of-interest data records based on the clustered subset groups of point-of-interest data records.

Abstract: Exemplary systems and methods perform post-processing operations on computer vision model detections of objects of interest in geospatial imagery to detect and assign attributes to the detected objects of interest. For example, an exemplary post-processing system correlates multiple detections, made by a computer vision model, of an object of interest depicted within a set of images of a geospatial location, determines, based on the correlated detections, an attribute of the object of interest depicted within the set of images of the geospatial location, and selects the attribute for inclusion in a dataset for the object of interest. Corresponding methods and systems are also disclosed.

Abstract: Exemplary systems and methods perform post-processing operations on computer vision model detections of objects of interest in geospatial imagery to detect and assign attributes to the detected objects of interest. For example, an exemplary post-processing system correlates multiple detections, made by a computer vision model, of an object of interest depicted within a set of images of a geospatial location, determines, based on the correlated detections, an attribute of the object of interest depicted within the set of images of the geospatial location, and selects the attribute for inclusion in a dataset for the object of interest. Corresponding methods and systems are also disclosed.

Abstract: An exemplary geospatial image processing system generates, based on multiple detections of an object of interest detected by a computer vision model in multiple, correlated images of a geospatial location captured from different camera viewpoints, user interface content that includes a visual indication of the detected object of interest superimposed at an object position on a view of the geospatial location. The system provides the user interface content for display in a graphical user interface view of a user interface and provides, by way of the user interface, a user interface tool configured to facilitate user validation of one or more of the multiple detections of the object of interest. The system may receive, a user validation of one or more of the multiple detections of the object of interest and may train the computer vision model based on the user validation. Corresponding methods and systems are also disclosed.

Abstract: Methods for improving data accuracy in a positioning system database using aerial imagery are provided. In one aspect, a method includes obtaining a two-dimensional image providing an aerial perspective of a building including a business, and receiving from a user a path identifier indicative of a virtual roadway proximal to the building, a first identifier in the first two-dimensional image of a first edge, second edge, and entrance of the business relative to the building. The method also includes determining first, second, and third latitude and longitude pairings on a map for the first identifier, second identifier, and third identifier, respectively, and providing, for display in the image, an identification of the first edge, second edge, and entrance of the business. Systems and machine-readable media are also provided.

Abstract: Methods for improving data accuracy in a positioning system database are provided. In one aspect, a method includes obtaining an image of a building including a business, and receiving from a user a first identifier in the image of a first edge of the business. The first identifier is associated with a first axis heading in the direction of the first edge of the business. The method also includes receiving from the user a second identifier of a second edge of the business, the second identifier associated with a second axis, receiving from the user a third identifier of an entrance to the business, the third identifier associated with a third axis, and identifying first, second, and third points on the first, second, and third axes, respectively, to identify the first edge, the second edge, and the entrance of the business on the map. Systems and machine-readable media are provided.