Abstract: A computer vision processor of a camera generates hyperzooms for persons or vehicles from image frames captured by the camera. The hyperzooms include a first hyperzoom associated with the persons or vehicles. The computer vision processor tracks traffic patterns of the persons or vehicles while obviating network usage by the camera by predicting positions of the persons or vehicles using a Kalman Filter from the first hyperzoom. The persons or vehicles are detected in the second hyperzoom. The positions of the persons or vehicles are updated based on detecting the persons or vehicles in the second hyperzoom. The first hyperzoom is removed from the camera. Tracks of the persons or vehicles are generated based on the updated positions. The second hyperzoom is removed from the camera. Track metadata is generated from the tracks for storing in a key-value database located on a non-transitory computer-readable storage medium of the camera.

Abstract: An electronic device includes an external panel material having an exterior visual characteristic that can be dynamically changed by a device-generated trigger. A controller of the device is communicatively coupled to at least one orientation sensor. The controller receives an input corresponding to a first context pre-identified as a condition that triggers a change in the exterior visual characteristic of the material. The controller identifies from sensor input received from the at least one orientation sensor whether the electronic device is in a first orientation that enables the external panel to be visible to a device user. In response to the electronic device being in the first orientation concurrently with receiving the input corresponding to the first context, the controller generates and transmits a change activation signal that changes the exterior visual characteristic of the external panel material from a first visible state to a second visible state.

Abstract: Embodiments disclosed herein relate generally to a customized or personalized GUL. More specifically, embodiments described herein disclose systems and process for deriving user preferences based upon previous actions of a set of users and using those user preferences to personalize one or more widgets within a GUL.

Abstract: Embodiments disclosed herein relate generally to a customized or personalized GUI. More specifically, embodiments described herein disclose systems and process for deriving user preferences based upon previous actions of a set of users and using those user preferences to personalize one or more widgets within a GUI.

Abstract: A computer vision processor of a camera generates hyperzooms for persons or vehicles from image frames captured by the camera. The hyperzooms include a first hyperzoom associated with the persons or vehicles. The computer vision processor tracks traffic patterns of the persons or vehicles while obviating network usage by the camera by predicting positions of the persons or vehicles using a Kalman Filter from the first hyperzoom. The persons or vehicles are detected in the second hyperzoom. The positions of the persons or vehicles are updated based on detecting the persons or vehicles in the second hyperzoom. The first hyperzoom is removed from the camera. Tracks of the persons or vehicles are generated based on the updated positions. The second hyperzoom is removed from the camera. Track metadata is generated from the tracks for storing in a key-value database located on a non-transitory computer-readable storage medium of the camera.

Abstract: A method provides techniques for modifying privilege modes on an electronic device based on circumstantial triggers. The method includes identifying, by at least one processor of an electronic device, a context corresponding to a circumstantial trigger. The method includes transitioning the electronic device from operating according to a first privilege mode to operating according to a second privilege mode in response to detecting a start of the circumstantial trigger. The method includes transitioning the electronic device from operating according to the second privilege mode to operating according to the first privilege mode in response to detecting an end of the circumstantial trigger.

Abstract: In some embodiments, a method comprises receiving, at a processor of an autonomous vehicle and from at least one sensor, sensor data distributed within a time window. A first event being a first event type occurring at a first time in the time window is identified by the processor using a software model based on the sensor data. At least one first attribute associated with the first event is extracted by the processor. A second event being the first event type occurring at a second time in the time window is identified by the processor based on the at least one first attribute. In response to determining that the second event is not yet recognized as being the first event type, a first label for the second event is generated by the processor.

Abstract: Methods, systems, and non-transitory computer-readable media are configured to perform operations comprising determining map data and detection data for an area in an environment; determining a change in the area based on the map data and the detection data; and generating control data based on the change.

Abstract: In implementations of systems for generating digital content, a computing device implements a generation system to receive a user input specifying a characteristic for digital content. The generation system generates input text based on the characteristic for processing by a first machine learning model. Output text generated by the first machine learning model based on processing the input text is received. The output text describes a digital content component. The generation system generates the digital content component by processing the output text using a second machine learning model. The generation system generates the digital content including the digital content component for display in a user interface based on the characteristic.

Abstract: In some embodiments, a method comprises receiving, at a processor of an autonomous vehicle and from at least one sensor, sensor data distributed within a time window. A first event being a first event type occurring at a first time in the time window is identified by the processor using a software model based on the sensor data. At least one first attribute associated with the first event is extracted by the processor. A second event being the first event type occurring at a second time in the time window is identified by the processor based on the at least one first attribute. In response to determining that the second event is not yet recognized as being the first event type, a first label for the second event is generated by the processor.

Abstract: A machine implemented method and system, including: receiving at a near real-time processor module, one or more tenant-specific business objects from a message handler module; receiving at the near real-time processor module, contextual data related to the received one or more tenant-specific business objects from a platform analytics module; forming at the near real-time processor module, one or more events by applying one or more pre-defined analytic models to the received contextual data and the received one or more tenant-specific business objects; receiving at a message publisher module, one or more events from the near real-time processor module; and transmitting the received one or more events to one or more subscribers for the one or more events.

Abstract: A computer vision processor of a camera extracts attributes of persons or vehicles from hyperzooms generated from image frames. The hyperzooms represent traffic patterns. The extracting is performed using a feature extractor of an on-camera convolutional neural network (CNN) including an inverted residual structure. The attributes include at least colors of clothing of the persons or colors of the vehicles. Mobile semantic segmentation models of the CNN are generated using the hyperzooms and the attributes. Attribute analytics are generated by executing the mobile semantic segmentation models while obviating network usage by the camera. The attribute analytics are stored in a key-value database located on a memory card of the camera. A query is received from the server instance specifying one or more of the attributes. The attribute analytics are filtered using the one or more of the attributes to obtain a portion of the traffic patterns.

Abstract: A computer vision processor of a camera generates hyperzooms for persons or vehicles from image frames captured by the camera. The hyperzooms include a first hyperzoom associated with the persons or vehicles. The computer vision processor tracks traffic patterns of the persons or vehicles while obviating network usage by the camera by predicting positions of the persons or vehicles using a Kalman Filter from the first hyperzoom. The persons or vehicles are detected in the second hyperzoom. The positions of the persons or vehicles are updated based on detecting the persons or vehicles in the second hyperzoom. The first hyperzoom is removed from the camera. Tracks of the persons or vehicles are generated based on the updated positions. The second hyperzoom is removed from the camera. Track metadata is generated from the tracks for storing in a key-value database located on a non-transitory computer-readable storage medium of the camera.

Abstract: Methods, systems, and non-transitory computer-readable media are configured to perform operations comprising determining map data and detection data for an area in an environment; determining a change in the area based on the map data and the detection data; and generating control data based on the change.

Abstract: A system and method for assisting entities or users to make decisions is disclosed. The user access the decision-making engine (MG Case composite) for end-to-end decision-making process. The system comprises a computing device (physical or on the cloud) having a processor and a memory, and a database. The engine comprises multiple modules such as case open, structure, MG Case matrix, brainstorming, problem solving, data analysis, speed math, and case end along with drive and alignment, integration and transition, and insights and impacts. The system is an integrated system and the modules are executed by the processor to perform an operation that draws on modules as needed. The decision-making engine interacts with internal and external facets of an organization, including users, various communication systems, ERPs, databases, etc. to execute various tasks related to decision making such as gathering data and driving the decision-making process through the organization or with the user.

Abstract: Various embodiments for customizing a dynamic navigation system are described herein. An embodiment operates by receiving a request from a support user device for debug access to an application. A predetermined time period for which to provision a set of computing resources is identified and the set of computing resources are provisioned for a pod on a server. Both a first container including access to a new instance of the application and a second container providing access to a debugger program are generated for the pod. Upon determining that the predetermined time period has expired, access to the provisioned set of computing resources of the pod is revoked, and the provisioned set of computing resources to be made available for other processes of the server.

Abstract: A method and related system operations include obtaining a video stream with an image sensor of a camera device, detecting a plurality of target objects by executing a neural network model based on the video stream with a vision processor unit of the camera device. The method also includes generating a plurality of bounding boxes, determining a plurality of character sequences by, for each respective bounding box of the plurality of bounding boxes, performing a set of optical character recognition (OCR) operations to determine a respective character sequence of the plurality of character sequences. The method also includes updating a plurality of tracklets to indicate the plurality of bounding boxes and storing the plurality of tracklets in association with the plurality of character sequences in a memory of the camera device.

Abstract: A machine implemented method and system, including: receiving at a near real-time processor module, one or more tenant-specific business objects from a message handler module; receiving at the near real-time processor module, contextual data related to the received one or more tenant-specific business objects from a platform analytics module; forming at the near real-time processor module, one or more events by applying one or more pre-defined analytic models to the received contextual data and the received one or more tenant-specific business objects; receiving at a message publisher module, one or more events from the near real-time processor module; and transmitting the received one or more events to one or more subscribers for the one or more events.

Abstract: In some embodiments, a computing system computes a hierarchical entity data model to facilitate autocompleting forms by generating an electronic schema extraction from an electronic form lacking data for one or more fields. The computing system generates an electronic schema including an input category and input field elements. The computing system accesses a hierarchical entity-data model including and entity category and entity-data elements. The computing system identifies associations between the entity category and input category based on semantic matching including text of an entity category label and an input field category label or matching a number of fields within an entity category to an input category. The computing system verifies the association by applying a natural language processing engine to the input field elements and the entity-data elements. The computing system autocompletes one or more input field elements with entity data from one or more of the entity-data elements.

Abstract: Aspects of the present disclosure control aging of a signal path in an idle mode to mitigate aging. In one example, an input of the signal path is alternately parked low and high over multiple idle periods to balance the aging of devices (e.g., transistors) in the signal path. In another example, a clock signal (e.g., a clock signal with a low frequency) is input to the signal path during idle periods to balance the aging of devices (e.g., transistors) in the signal path. In another example, the input of the signal path is parked high or low during each idle period based on an aging pattern.