Abstract: In various examples, object detections of a machine learning model are leveraged to automatically generate new ground truth data for images captured at different perspectives. The machine learning model may generate a prediction of a detected object at the different perspective, and an object tracking algorithm may be used to track the object through other images in a sequence of images where the machine learning model may not have detected the object. New ground truth data may be generated as a result of the object tracking algorithms outputs, and the new ground truth data may be used to retrain or update the machine learning model, train a different machine learning model, or increase the robustness of a ground truth data set that may be used for training machine learning models from various perspectives.

Abstract: In various examples, object detections of a machine learning model are leveraged to automatically generate new ground truth data for images captured at different perspectives. The machine learning model may generate a prediction of a detected object at the different perspective, and an object tracking algorithm may be used to track the object through other images in a sequence of images where the machine learning model may not have detected the object. New ground truth data may be generated as a result of the object tracking algorithms outputs, and the new ground truth data may be used to retrain or update the machine learning model, train a different machine learning model, or increase the robustness of a ground truth data set that may be used for training machine learning models from various perspectives.

Abstract: In various examples, object detections of a machine learning model are leveraged to automatically generate new ground truth data for images captured at different perspectives. The machine learning model may generate a prediction of a detected object at the different perspective, and an object tracking algorithm may be used to track the object through other images in a sequence of images where the machine learning model may not have detected the object. New ground truth data may be generated as a result of the object tracking algorithms outputs, and the new ground truth data may be used to retrain or update the machine learning model, train a different machine learning model, or increase the robustness of a ground truth data set that may be used for training machine learning models from various perspectives.

Abstract: In various examples, object detections of a machine learning model are leveraged to automatically generate new ground truth data for images captured at different perspectives. The machine learning model may generate a prediction of a detected object at the different perspective, and an object tracking algorithm may be used to track the object through other images in a sequence of images where the machine learning model may not have detected the object. New ground truth data may be generated as a result of the object tracking algorithms outputs, and the new ground truth data may be used to retrain or update the machine learning model, train a different machine learning model, or increase the robustness of a ground truth data set that may be used for training machine learning models from various perspectives.

Abstract: A beacon discovery system can utilize one or more automated devices to wirelessly identify a location of one or more beacons positioned in an out-of-site location. Intelligent execution of a detection strategy by a detection module of the beacon discovery system can provide fast and efficient recovery of a beacon by adaptively utilizing multiple different automation and wireless positioning technologies.

Abstract: In various examples, object detections of a machine learning model are leveraged to automatically generate new ground truth data for images captured at different perspectives. The machine learning model may generate a prediction of a detected object at the different perspective, and an object tracking algorithm may be used to track the object through other images in a sequence of images where the machine learning model may not have detected the object. New ground truth data may be generated as a result of the object tracking algorithms outputs, and the new ground truth data may be used to retrain or update the machine learning model, train a different machine learning model, or increase the robustness of a ground truth data set that may be used for training machine learning models from various perspectives.

Abstract: A system and method for controlling a computer-based instrumentation system which provides simplified application development and improved performance for instrumentation systems. The present invention provides a system including a software architecture which defines the control and management of an instrumentation system. The present invention includes a base object class, an object manager, session and resource classes, and one or more resource templates. The instrumentation system of the present invention provides a plurality of instrument control resources which are used as building blocks to create instrument drivers and higher level applications. The present invention also uses object oriented technology which allows device resources to be easily combined to create higher level applications. The present invention is independent of I/O interface type, operating system, and programming language while also providing a common look and feel and consistent API to the user.

Abstract: A method and apparatus for controlling instrumentation systems and for providing a user with the capability to develop instrument drivers and application software for controlling instrumentation systems. The present invention provides a system including a software architecture which defines the control and management of an instrumentation system. The method of the present invention utilizes a device resource independence approach whereby the individual capabilities of devices are broken down into a plurality of objects called resources and these resources are then used to develop instrument drivers or instrument control applications. The method of the present invention also uses object oriented technology which allows device resources to be easily combined to create higher level applications. The present invention is independent of I/O interface type, operating system, and programming language while also providing a common look and feel and consistent API to the user.

Abstract: A system and method for improved handling of events in an instrumentation system which provides numerous features and advantages over prior art methods. The present invention provides simplified application development and improved performance for instrumentation systems. The instrumentation system of the present invention provides event queueing, event handling, and suspend handling features, thus providing the user or developer with greater freedom in designing his test and measurement or process control application. The present invention includes a single operation referred to as viEnableEvent which is used for enabling events of all event types, and a single operation for installing handlers for all event types, referred to as viInstallHandlr. The operation viEnableEvent includes one or more parameters which can be specified as a filter to qualify the types of events desired to be received at the time of the event occurrence.

Abstract: A system and method for developing instrument drivers and applications in a computer-based instrumentation system. The present invention provides simplified application development and improved performance for instrumentation systems. The instrumentation system of the present invention provides a plurality of instrument control resources which are used as building blocks to create instrument drivers and higher level applications. The present invention also uses object oriented technology which allows device resources to be easily combined to create higher level applications. The present invention is independent of I/O interface type, operating system, and programming language while also providing a common look and feel and consistent API to the user. A developer creates a resource in the VISA system by first determining if the desired resource can inherit from a currently existing resource.