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    Techniques for detecting changes to circuit delays in telecommunications networks
    41.
    发明授权
    Techniques for detecting changes to circuit delays in telecommunications networks 有权

    公开(公告)号：US11665075B2

    公开(公告)日：2023-05-30

    申请号：US17689864

    申请日：2022-03-08

    Applicant: NETFLIX, INC.

    Inventor： David Bannister ,  Rafael Rodriguez

    IPC: H04L43/0864 ,  H04B10/27 ,  H04L41/06 ,  H04L43/10 ,  H04L69/16

    CPC classification number: H04L43/0864 ,  H04B10/27 ,  H04L41/06 ,  H04L43/10 ,  H04L69/16

    Abstract: In various embodiments, a monitoring application assesses delays associated with a circuit within a network. The monitoring application determines a measured trip time between a first device and a second device that is connected to the first device via the circuit. The measured trip time is associated with a first variance attributable to the first device. The monitoring application performs one or more digital signal processing operations based on the measured trip time to generate a predicted trip time. The predicted trip time is associated with a second variance attributable to the first device that is less than the first variance. Based on the predicted trip time, the monitoring application determines characteristic(s) of the delay associated with the circuit. Advantageously, reducing variations attributable to the first device when generating the first predicted trip time increases the accuracy with which the monitoring application can determine the characteristic(s) of the delay.

    TECHNIQUES FOR JOINTLY TRAINING A DOWNSCALER AND AN UPSCALER FOR VIDEO STREAMING
    43.
    发明公开
    TECHNIQUES FOR JOINTLY TRAINING A DOWNSCALER AND AN UPSCALER FOR VIDEO STREAMING 审中-公开

    公开(公告)号：US20230144735A1

    公开(公告)日：2023-05-11

    申请号：US17981281

    申请日：2022-11-04

    Applicant: NETFLIX, INC.

    Inventor： Christos G. BAMPIS ,  Zhi LI

    IPC: G06T3/40

    CPC classification number: G06T3/4046

    Abstract: In various embodiments a training application trains convolutional neural networks (CNNs) to reduce reconstruction errors. The training application executes a first CNN on a source image having a first resolution to generate a downscaled image having a second resolution. The training application executes a second CNN on the downscaled image to generate a reconstructed image having the first resolution. The training application computes a reconstruction error based on the reconstructed image and the source image. The training application updates a first learnable parameter value included in the first CNN based on the reconstruction error to generate at least a partially trained downscaling CNN. The training application updates a second learnable parameter included in the second CNN based on the reconstruction error to generate at least a partially trained upscaling CNN.

    Machine-assisted translation for subtitle localization
    44.
    发明授权
    Machine-assisted translation for subtitle localization 有权

    公开(公告)号：US11636273B2

    公开(公告)日：2023-04-25

    申请号：US16442403

    申请日：2019-06-14

    Applicant: NETFLIX, INC.

    Inventor： Ballav Bihani ,  Matthew James Rickard ,  Marianna Semeniakin ,  Ranjith Kumar Shetty ,  Allison Filemyr Smith ,  Patrick Brendon Pearson ,  Sameer Shah

    IPC: G06F40/58 ,  G10L15/26

    Abstract: One embodiment of the present disclosure sets forth a technique for generating translation suggestions. The technique includes receiving a sequence of source-language subtitle events associated with a content item, where each source-language subtitle event includes a different textual string representing a corresponding portion of the content item, generating a unit of translatable text based on a textual string included in at least one source-language subtitle event from the sequence, translating, via software executing on a machine, the unit of translatable text into target-language text, generating, based on the target-language text, at least one target-language subtitle event associated with a portion of the content item corresponding to the at least one source-language subtitle event, and generating, for display, a subtitle presentation template that includes the at least one target-language subtitle event.

    EFFICIENT ENCODING OF FILM GRAIN NOISE
    46.
    发明申请
    EFFICIENT ENCODING OF FILM GRAIN NOISE 有权

    公开(公告)号：US20230059035A1

    公开(公告)日：2023-02-23

    申请号：US17409580

    申请日：2021-08-23

    Applicant: NETFLIX, INC.

    Inventor： Anush MOORTHY ,  Andrey NORKIN

    IPC: H04N19/85 ,  H04N19/52 ,  H04N19/176 ,  H04N19/593 ,  H04N19/172 ,  H04N19/80 ,  H04N19/147

    Abstract: One embodiment of the present invention sets forth a technique for encoding video frames. The technique includes performing one or more operations to generate a plurality of denoised video frames associated with a video sequence. The technique also includes determining a first set of motion vectors based on a first denoised frame included in the plurality of denoised video frames and a second denoised frame included in the plurality of denoised video frames, and determining a first residual between the second denoised frame and a prediction frame associated with the second denoised frame. The technique further includes performing one or more operations to generate an encoded video frame associated with the second denoised frame based on the first set of motion vectors, the first residual, and a first frame that is included in the video sequence and corresponds to the first denoised frame.

    Machine learning techniques for component-based image preprocessing
    47.
    发明授权
    Machine learning techniques for component-based image preprocessing 有权

    公开(公告)号：US11563986B1

    公开(公告)日：2023-01-24

    申请号：US17551086

    申请日：2021-12-14

    Applicant: NETFLIX, INC.

    Inventor： Christos G. Bampis ,  Li-Heng Chen ,  Aditya Mavlankar ,  Anush Moorthy

    IPC: H04N19/86 ,  H04N19/186 ,  H04N19/30 ,  H04N19/132 ,  G06N3/04 ,  H04N19/89

    Abstract: In various embodiments, a training application trains a machine learning model to preprocess images. In operation, the training application computes a chroma sampling factor based on a downscaling factor and a chroma subsampling ratio. The training application executes a machine learning model that is associated with the chroma sampling factor on data that corresponds to both an image and a first chroma component to generate preprocessed data corresponding to the first chroma component. Based on the preprocessed data, the training application updates at least one parameter of the machine learning model to generate a trained machine learning model that is associated with the first chroma component.

    SYSTEMS AND METHODS FOR PROVIDING OPTIMIZED TIME SCALES AND ACCURATE PRESENTATION TIME STAMPS
    48.
    发明申请
    SYSTEMS AND METHODS FOR PROVIDING OPTIMIZED TIME SCALES AND ACCURATE PRESENTATION TIME STAMPS 有权

    公开(公告)号：US20220417620A1

    公开(公告)日：2022-12-29

    申请号：US17359468

    申请日：2021-06-25

    Applicant: Netflix, Inc.

    Inventor： Weiguo Zheng ,  Rex Yik Chun Ching ,  Yongjun Jeon ,  Chandrika Kasi

    IPC: H04N21/8547 ,  G11B27/34 ,  H04N21/2343

    Abstract: The disclosed computer-implemented method includes determining, for multiple different media items, a current time scale at which the media items are encoded for distribution, where at least two of the media items are encoded at different frame rates. The method then includes identifying, for the media items, a unified time scale that provides a constant frame interval for each of the media items. The method also includes changing at least one of the media items from the current time scale to the identified unified time scale to provide a constant frame interval for the changed media item(s). Various other methods, systems, and computer-readable media are also disclosed.

    Techniques for optimizing encoding tasks
    49.
    发明授权
    Techniques for optimizing encoding tasks 有权

    公开(公告)号：US11539966B2

    公开(公告)日：2022-12-27

    申请号：US17141067

    申请日：2021-01-04

    Applicant: NETFLIX, INC.

    Inventor： Anush Moorthy ,  Megha Manohara

    IPC: H04N19/179 ,  H04N19/436 ,  H04N19/115 ,  H04N19/85 ,  H04N21/845 ,  H04N19/146

    Abstract: In various embodiments, a shot collation application causes multiple encoding instances to encode a source video sequence that includes at least two shot sequences. The shot collation application assigns a first shot sequence to a first chunk. Subsequently, the shot collation application determines that a second shot sequence does not meet a collation criterion with respect to the first chunk. Consequently, the shot collation application assigns the second shot sequence or a third shot sequence derived from the second shot sequence to a second chunk. The shot collation application causes a first encoding instance to independently encode each shot sequence assigned to the first chunk. Similarly, the shot collation application causes a second encoding instance to independently encode each shot sequence assigned to the second chunk. Finally, a chunk assembler combines the first encoded chunk and the second encoded chunk to generate an encoded video sequence.

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