Abstract: Online meeting software typically generates a flow of data. A server system is configured to receive the flow of data, which may include metadata. The data may include metadata of online meetings. Different types of metadata are generated by online meetings. Such different types of metadata are provided in different patterns. Different types of metadata are provided throughout the online meeting session or at various points of the session and are provided to various different elements of the server system. The various different metadata received are then parsed and certain specific metadata elements are identified to match the different metadata streams.

Abstract: A method of training a neural network for detecting target features in images is described. The neural network is trained using a first data set that includes labeled images, where at least some of the labeled images having subjects with labeled features, including: dividing each of the labeled images of the first data set into a respective plurality of tiles, and generating, for each of the plurality of tiles, a plurality of feature anchors that indicate target features within the corresponding tile. Target features that correspond to the plurality of feature anchors are detected in a second data set of unlabeled images. Images of the second data set having target features that were not detected are labeled. A third data set that includes the first data set and the labeled images of the second data set is generated. The neural network is trained using the third data set.

Abstract: A method of training a neural network for detecting target features in images is described. The neural network is trained using a first data set that includes labeled images, where at least some of the labeled images having subjects with labeled features, including: dividing each of the labeled images of the first data set into a respective plurality of tiles, and generating, for each of the plurality of tiles, a plurality of feature anchors that indicate target features within the corresponding tile. Target features that correspond to the plurality of feature anchors are detected in a second data set of unlabeled images. Images of the second data set having target features that were not detected are labeled. A third data set that includes the first data set and the labeled images of the second data set is generated. The neural network is trained using the third data set.

Abstract: A graphics server and method for streaming rendered content via a remote graphics rendering service is provided. In one embodiment, the server includes a memory, a graphics renderer, a frame capturer, an encoder, and a processor. The memory is configured to store a pre-computed skip-frame message indicative to a client to re-use a previously transmitted frame of the video stream. The graphics renderer is configured to identify when rendered content has not changed. When the graphics renderer identifies that the rendered content has not changed, the processor is configured to cause: (1) the frame capturer to not capture the frames of the rendered content; (2) the encoder to not encode the frames of the rendered content; and (3) the pre-encoded skip-frame message to be transmitted without requiring any pixel processing.

Abstract: A graphics server and method for streaming rendered content via a remote graphics rendering service is provided. In one embodiment, the server includes a memory, a graphics renderer, a frame capturer, an encoder, and a processor. The memory is configured to store a pre-computed skip-frame message indicative to a client to re-use a previously transmitted frame of the video stream. The graphics renderer is configured to identify when rendered content has not changed. When the graphics renderer identifies that the rendered content has not changed, the processor is configured to cause: (1) the frame capturer to not capture the frames of the rendered content; (2) the encoder to not encode the frames of the rendered content; and (3) the pre-encoded skip-frame message to be transmitted without requiring any pixel processing.