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公开(公告)号：US20200068253A1
公开(公告)日：2020-02-27
申请号：US16109755
申请日：2018-08-23
Applicant: DISH Network L.L.C.
Inventor： Ilhyoung Kim , Pratik Divanji , Abhijit Y. Sharma , Swapnil Tilaye
Abstract: Novel techniques are described for automated transition classification for binge watching of content. For example, a number of frame images is extracted from a candidate segment time window of content. The frame images can automatically be classified by a trained machine learning model into segment and non-segment classifications, and the classification results can be represented by a two-dimensional (2D) image. The 2D image can be run through a multi-level convolutional conversion to output a set of output images, and a serialized representation of the output images can be run through a trained computational neural network to generate a transition array, from which a candidate transition time can be derived (indicating a precise time at which the content transitions to the classified segment).
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公开(公告)号：US10694244B2
公开(公告)日：2020-06-23
申请号：US16109755
申请日：2018-08-23
Applicant: DISH Network L.L.C.
Inventor： Ilhyoung Kim , Pratik Divanji , Abhijit Y. Sharma , Swapnil Tilaye
Abstract: Novel techniques are described for automated transition classification for binge watching of content. For example, a number of frame images is extracted from a candidate segment time window of content. The frame images can automatically be classified by a trained machine learning model into segment and non-segment classifications, and the classification results can be represented by a two-dimensional (2D) image. The 2D image can be run through a multi-level convolutional conversion to output a set of output images, and a serialized representation of the output images can be run through a trained computational neural network to generate a transition array, from which a candidate transition time can be derived (indicating a precise time at which the content transitions to the classified segment).
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公开(公告)号：US20200267443A1
公开(公告)日：2020-08-20
申请号：US16870073
申请日：2020-05-08
Applicant: DISH Network L.L.C.
Inventor： Ilhyoung Kim , Pratik Divanji , Abhijit Y. Sharma , Swapnil Tilaye
Abstract: Novel techniques are described for automated transition classification for binge watching of content. For example, a number of frame images is extracted from a candidate segment time window of content. The frame images can automatically be classified by a trained machine learning model into segment and non-segment classifications, and the classification results can be represented by a two-dimensional (2D) image. The 2D image can be run through a multi-level convolutional conversion to output a set of output images, and a serialized representation of the output images can be run through a trained computational neural network to generate a transition array, from which a candidate transition time can be derived (indicating a precise time at which the content transitions to the classified segment).
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公开(公告)号：US11019394B2
公开(公告)日：2021-05-25
申请号：US16870073
申请日：2020-05-08
Applicant: DISH Network L.L.C.
Inventor： Ilhyoung Kim , Pratik Divanji , Abhijit Y. Sharma , Swapnil Tilaye
Abstract: Novel techniques are described for automated transition classification for binge watching of content. For example, a number of frame images is extracted from a candidate segment time window of content. The frame images can automatically be classified by a trained machine learning model into segment and non-segment classifications, and the classification results can be represented by a two-dimensional (2D) image. The 2D image can be run through a multi-level convolutional conversion to output a set of output images, and a serialized representation of the output images can be run through a trained computational neural network to generate a transition array, from which a candidate transition time can be derived (indicating a precise time at which the content transitions to the classified segment).
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