PICTURES AND LAYERS INCLUDED IN A VVC IMAGE ITEM

    公开(公告)号:US20220070495A1

    公开(公告)日:2022-03-03

    申请号:US17464364

    申请日:2021-09-01

    Applicant: Lemon Inc.

    Abstract: Systems, methods and apparatus for processing image data are described. One example method includes performing a conversion between a visual media file and a bitstream. The visual media file comprises a sequence of one or more pictures according to a media file format, and the bitstream comprises one or more access units according to a video coding format. The bitstream is coded according to the video coding format. The media file format specifies that an image item of a specific type value in the visual media file includes a single access unit of the bitstream. The single access unit is either an Intra Random Access Picture (IRAP) access unit or a Gradual Decoding Refresh (GDR) access unit according to the video coding format. All pictures in the GDR access unit are identified as a recovery point in the bitstream.

    Methods and systems for garbage collection and compaction for key-value engines

    公开(公告)号:US12298900B2

    公开(公告)日:2025-05-13

    申请号:US18475664

    申请日:2023-09-27

    Abstract: Methods and systems for garbage collection and compaction for key-value engines in a data storage and communication system. The method includes determining disk capacity usage of the key-value engine and adjusting a garbage collection percentage threshold and a number of garbage collection threads based on whether the disk capacity usage of the key-value engine meets and/or exceeds predetermined disk capacity usage thresholds. The method may further include performing a periodic compaction process to consolidate one or more expired pages of one or more applications on a log-structured merge (LSM) tree by merging one or more layers into a last layer of the one or more expired pages to reduce data handling during an occurrence of the garbage collection.

    GENERATING AUDIO REPRESENTATIONS USING MACHINE LEARNING MODEL

    公开(公告)号:US20250140242A1

    公开(公告)日:2025-05-01

    申请号:US18385749

    申请日:2023-10-31

    Applicant: Lemon Inc.

    Abstract: The present disclosure describes techniques for generating audio representations using a machine learning model. A machine learning model is pre-trained using unlabeled audio data. The pre-training enables the machine learning model to recognize audio patterns and generate initial audio representations. The machine learning model is refined by a task-specific fine-tuning process using labeled data. The task-specific fine-tuning process incorporates multi-task learning heads to optimize the machine learning model. The task-specific fine-tuning process enables the machine learning model to be specialized in specific audio tasks and generate continuous audio representations. The continuous audio representations retain acoustic nuances and subtleties of audio signals. The machine learning model is configured and enabled to generate quantized audio representations by incorporating vector quantization to the task-specific fine-tuning process.

    VIDEO GENERATION METHOD, AND TRAINING METHOD FOR VIDEO GENERATION MODEL

    公开(公告)号:US20250131613A1

    公开(公告)日:2025-04-24

    申请号:US18834154

    申请日:2022-12-15

    Applicant: Lemon Inc.

    Abstract: Provided in the embodiments of the present disclosure are a video generation method, and a training method for a video generation model. The video generation method includes: acquiring a first video, wherein the first video includes a first object image; and inputting the first video into a pre-trained video generation model to obtain a second video, wherein the video generation model is obtained by means of performing training on the basis of a target image and a plurality of sample image pairs obtained from a plurality of first sample images, an object image in the second video is generated on the basis of a preset animal image in the target image and the first object image, and a background image of the second video is generated on the basis of a first background image of the first video.

    METHODS AND SYSTEMS FOR LIVE STREAMING RECOMMENDED CONTENT

    公开(公告)号:US20250126306A1

    公开(公告)日:2025-04-17

    申请号:US19002575

    申请日:2024-12-26

    Applicant: Lemon Inc.

    Abstract: A method for live streaming recommended content from a content request includes live streaming a first content from a first user side, activating a live reaction at the first user side, and providing the content request at a second user side when the live reaction is enabled. The method also includes determining a second content, sending the content request indicating the second content, and receiving a confirmation at the second user side indicating the content request being sent. The method further includes receiving, at the first user side, the content request sent from the second user side, approving the content request at the first user side, and after the content request is approved, live streaming from the first user side, the second content corresponding to the content request.

    METHOD AND DEVICE, ELECTRONIC EQUIPMENT AND STORAGE MEDIUM FOR TRAINING AND OPTIMIZING ANALYSIS MODEL

    公开(公告)号:US20250125020A1

    公开(公告)日:2025-04-17

    申请号:US18896056

    申请日:2024-09-25

    Abstract: The embodiment of the invention provides method, apparatus, device and a storage medium for training and optimizing an analysis model. The method of optimizing the analysis model includes: fine-tuning an analysis model with a first set of values regarding a first property of a target material to determine a second set of values regarding a second property of the target material; determining an association between the first property and the second property of the target material based on a first set of values and a second set of values; determining a target value of the target material regarding the first property with the association based on a reference value of the target material regarding the second property, the reference value being determined based on an experiment on target material; and optimizing the analysis model with the target value of the target material regarding the first property. In this way, embodiments of the present disclosure can utilize limited experimental data to optimize the analysis model.

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