Abstract: A method for image generation, preferably including: generating a set of mission parameters for a UAV mission of the UAV associated with aerial scanning of a region of interest; controlling the UAV to perform the mission; generating an image subassembly corresponding to the mission; and/or rendering the image subassembly at a display.

Abstract: Aspects of the present disclosure are directed to an artificial reality system orchestrating interactions between virtual object “augments.” The orchestration can include linking, which can be forming two or more augments into a combination, embedding an augment within an existing combination, or triggering an action mapped to the linking of those augments. Another type of orchestration can include extracting, which can refer to taking an augment out of an existing combination, either by removing it from the combination or copying the augment to leave a version in the combination and having another version outside the combination.

Abstract: Aspects of the present disclosure are directed to an artificial reality system orchestrating interactions between virtual object “augments.” The orchestration can include linking, which can be forming two or more augments into a combination, embedding an augment within an existing combination, or triggering an action mapped to the linking of those augments. Another type of orchestration can include extracting, which can refer to taking an augment out of an existing combination, either by removing it from the combination or copying the augment to leave a version in the combination and having another version outside the combination.

Abstract: A method for image generation, preferably including: generating a set of mission parameters for a UAV mission of the UAV associated with aerial scanning of a region of interest; controlling the UAV to perform the mission; generating an image subassembly corresponding to the mission; and/or rendering the image subassembly at a display.

Abstract: A method for adaptive mission execution by an unmanned aerial vehicle includes receiving a set of pre-calculated mission parameters corresponding to an initial UAV mission; collecting UAV operation data during flight of the unmanned aerial vehicle; calculating a set of modified mission parameters from the set of pre-calculated mission parameters and the UAV operation data, the set of modified mission parameters corresponding to a modified UAV mission; and executing the modified UAV mission on the unmanned aerial vehicle.

Abstract: A method for image generation, preferably including: generating a set of mission parameters for a UAV mission of the UAV associated with aerial scanning of a region of interest; controlling the UAV to perform the mission; generating an image subassembly corresponding to the mission; and/or rendering the image subassembly at a display.

Abstract: A method for adaptive mission execution by an unmanned aerial vehicle includes receiving a set of pre-calculated mission parameters corresponding to an initial UAV mission; collecting UAV operation data during flight of the unmanned aerial vehicle; calculating a set of modified mission parameters from the set of pre-calculated mission parameters and the UAV operation data, the set of modified mission parameters corresponding to a modified UAV mission; and executing the modified UAV mission on the unmanned aerial vehicle.

Abstract: Examples described herein generally relate to a computer system for generating a knowledge graph storing a plurality of entities and to displaying a topic page for an entity in the knowledge graph. The computer system performs a mining of source documents within an enterprise intranet to determine a plurality of entity names. The computer system generates an entity record within the knowledge graph for a mined entity name based on an entity schema and the source documents. The entity record includes attributes aggregated from the source documents. The computer system receives a curation action on the entity record from a first user. The computer system updates the entity record based on the curation action. The computer system displays an entity page including at least a portion of the attributes to a second user based on permissions of the second user to view the source documents.

Abstract: A method for image generation, preferably including: generating a set of mission parameters for a UAV mission of the UAV associated with aerial scanning of a region of interest; controlling the UAV to perform the mission; generating an image subassembly corresponding to the mission; and/or rendering the image subassembly at a display.

Abstract: A method for image generation, preferably including: generating a set of mission parameters for a UAV mission of the UAV associated with aerial scanning of a region of interest; controlling the UAV to perform the mission; generating an image subassembly corresponding to the mission; and/or rendering the image subassembly at a display.

Abstract: Examples described herein generally relate to a computer system including a knowledge graph storing a plurality of entities. The computer system generates an Aho Corasick trie including an entity name for each of the plurality of entities in the knowledge graph. The computer system compares a document viewed by a user to a plurality of templates defining potential entity names to identify extracts of the document matching at least one of the plurality of templates. The computer system applies the document to the Aho Corasick trie to determine potential entity names within the document that each match a respective one of the plurality of entities in the knowledge graph. The computer system annotates one or more matching entity names within the document with information from the knowledge graph for the respective ones of the plurality of entities to show, for example, a topic card providing information about the respective entities.

Abstract: Examples described herein generally relate to a computer system including a knowledge graph storing a plurality of entities. The computer system compares source documents within an enterprise intranet to a plurality of templates defining potential entity attributes to identify extracts matching at least one of the plurality of templates. The computer system parses the extracts according to respective templates of the plurality of templates that match the extracts to determine instances. The computer system performs incremental clustering on a number of the instances to determine potential entity names. The computer system queries the knowledge graph with the potential entity names to obtain a set of candidate entity records. The computer system links the potential entity names with at least partial matching ones of the set of candidate entity records to define updated matching candidate entity records. The computer system updates the knowledge graph with the updated matching candidate entity records.

Abstract: A method for image generation, preferably including: generating a set of mission parameters for a UAV mission of the UAV associated with aerial scanning of a region of interest; controlling the UAV to perform the mission; generating an image subassembly corresponding to the mission; and/or rendering the image subassembly at a display.

Abstract: A method for adaptive mission execution by an unmanned aerial vehicle includes receiving a set of pre-calculated mission parameters corresponding to an initial UAV mission; collecting UAV operation data during flight of the unmanned aerial vehicle; calculating a set of modified mission parameters from the set of pre-calculated mission parameters and the UAV operation data, the set of modified mission parameters corresponding to a modified UAV mission; and executing the modified UAV mission on the unmanned aerial vehicle.

Abstract: A method for image generation, preferably including: generating a set of mission parameters for a UAV mission of the UAV associated with aerial scanning of a region of interest; controlling the UAV to perform the mission; generating an image subassembly corresponding to the mission; and/or rendering the image subassembly at a display.

Abstract: A method for adaptive mission execution by an unmanned aerial vehicle includes receiving a set of pre-calculated mission parameters corresponding to an initial UAV mission; collecting UAV operation data during flight of the unmanned aerial vehicle; calculating a set of modified mission parameters from the set of pre-calculated mission parameters and the UAV operation data, the set of modified mission parameters corresponding to a modified UAV mission; and executing the modified UAV mission on the unmanned aerial vehicle.

Abstract: Examples described herein generally relate to a computer system including a knowledge graph storing a plurality of entities. The computer system generates an Aho Corasick trie including an entity name for each of the plurality of entities in the knowledge graph. The computer system compares a document viewed by a user to a plurality of templates defining potential entity names to identify extracts of the document matching at least one of the plurality of templates. The computer system applies the document to the Aho Corasick trie to determine potential entity names within the document that each match a respective one of the plurality of entities in the knowledge graph. The computer system annotates one or more matching entity names within the document with information from the knowledge graph for the respective ones of the plurality of entities to show, for example, a topic card providing information about the respective entities.

Abstract: Examples described herein generally relate to a computer system for generating a knowledge graph storing a plurality of entities and to displaying a topic page for an entity in the knowledge graph. The computer system performs a mining of source documents within an enterprise intranet to determine a plurality of entity names. The computer system generates an entity record within the knowledge graph for a mined entity name based on an entity schema and the source documents. The entity record includes attributes aggregated from the source documents. The computer system receives a curation action on the entity record from a first user. The computer system updates the entity record based on the curation action. The computer system displays an entity page including at least a portion of the attributes to a second user based on permissions of the second user to view the source documents.

Abstract: Examples described herein generally relate to a computer system including a knowledge graph storing a plurality of entities. The computer system compares source documents within an enterprise intranet to a plurality of templates defining potential entity attributes to identify extracts matching at least one of the plurality of templates. The computer system parses the extracts according to respective templates of the plurality of templates that match the extracts to determine instances. The computer system performs incremental clustering on a number of the instances to determine potential entity names. The computer system queries the knowledge graph with the potential entity names to obtain a set of candidate entity records. The computer system links the potential entity names with at least partial matching ones of the set of candidate entity records to define updated matching candidate entity records. The computer system updates the knowledge graph with the updated matching candidate entity records.

Abstract: Memory facilitation using directed acyclic graphs is described, for example, where a plurality of directed acyclic graphs are trained for gesture recognition from human skeletal data, or to estimate human body joint positions from depth images for gesture detection. In various examples directed acyclic graphs are grown during training using a training objective which takes into account both connection patterns between nodes and split function parameter values. For example, a layer of child nodes is grown and connected to a parent layer of nodes using an initialization strategy. In examples, various local search processes are used to find good combinations of connection patterns and split function parameters.