Other

Arris Enterprises LLC

Cogniac, Corp.

Yui Ming Tsang

Sandip C Patel

William S Kish

Huayan Wang

A computer system may train and use a machine-learning model to quantitatively analyze an image. In particular, the computer system may generate the machine-learning model based on a set of reference images that include content with instances of a quantitative feature attribute and one or more feedback metrics that specify locations of the instances of the quantitative feature attribute in the reference images and numerical values associated with the instances of the quantitative feature attribute. Then, after receiving the image from an electronic device, the computer system may analyze the image using the machine-learning model to perform measurements of one or more additional instances of the quantitative feature attribute in the image. Moreover, the computer system may provide a measurement result for the image, the measurement result including a second numerical value associated with the one or more additional instances of the quantitative feature attribute in the image.

Machine-learning measurements of quantitative feature attributes

In order to determine a sounding interval, an electronic device iteratively revises a set of potential sounding intervals based on transmission statistics associated with communication of some packets with and other packets without transmission beamforming for the set of potential sounding intervals. In particular, the electronic device calculates rank positions for the set of potential sounding intervals based on an estimated throughput and numbers of packets transmitted with transmission beamforming for the set of potential sounding intervals out of a total number of packets transmitted. Then, the electronic device may determine the output sounding interval based on the ranking. When the convergence criterion is achieved, the electronic device may determine a moment based on calculated frequencies of the rank positions over multiple iterations, which is used to revise the set of potential sounding intervals in the next iteration.

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Redwood City, CA, United States of America

Yui Ming Tsang