CONSTRAINTS AND UNIT TYPES TO SIMPLIFY VIDEO RANDOM ACCESS
Granted: November 28, 2024
Application Number:
20240397096
Disclosed herein are innovations for bitstreams having clean random access (CRA) pictures and/or other types of random access point (RAP) pictures. New type definitions and strategic constraints on types of RAP pictures can simplify mapping of units of elementary video stream data to a container format. Such innovations can help improve the ability for video coding systems to more flexibly perform adaptive video delivery, production editing, commercial insertion, and the like.
CONSTRAINTS AND UNIT TYPES TO SIMPLIFY VIDEO RANDOM ACCESS
Granted: November 28, 2024
Application Number:
20240397105
Disclosed herein are innovations for bitstreams having clean random access (CRA) pictures and/or other types of random access point (RAP) pictures. New type definitions and strategic constraints on types of RAP pictures can simplify mapping of units of elementary video stream data to a container format. Such innovations can help improve the ability for video coding systems to more flexibly perform adaptive video delivery, production editing, commercial insertion, and the like.
CONSTRAINTS AND UNIT TYPES TO SIMPLIFY VIDEO RANDOM ACCESS
Granted: November 28, 2024
Application Number:
20240397104
Disclosed herein are innovations for bitstreams having clean random access (CRA) pictures and/or other types of random access point (RAP) pictures. New type definitions and strategic constraints on types of RAP pictures can simplify mapping of units of elementary video stream data to a container format. Such innovations can help improve the ability for video coding systems to more flexibly perform adaptive video delivery, production editing, commercial insertion, and the like.
CONSTRAINTS AND UNIT TYPES TO SIMPLIFY VIDEO RANDOM ACCESS
Granted: November 28, 2024
Application Number:
20240397103
Disclosed herein are innovations for bitstreams having clean random access (CRA) pictures and/or other types of random access point (RAP) pictures. New type definitions and strategic constraints on types of RAP pictures can simplify mapping of units of elementary video stream data to a container format. Such innovations can help improve the ability for video coding systems to more flexibly perform adaptive video delivery, production editing, commercial insertion, and the like.
CONSTRAINTS AND UNIT TYPES TO SIMPLIFY VIDEO RANDOM ACCESS
Granted: November 28, 2024
Application Number:
20240397102
Disclosed herein are innovations for bitstreams having clean random access (CRA) pictures and/or other types of random access point (RAP) pictures. New type definitions and strategic constraints on types of RAP pictures can simplify mapping of units of elementary video stream data to a container format. Such innovations can help improve the ability for video coding systems to more flexibly perform adaptive video delivery, production editing, commercial insertion, and the like.
CONSTRAINTS AND UNIT TYPES TO SIMPLIFY VIDEO RANDOM ACCESS
Granted: November 28, 2024
Application Number:
20240397101
Disclosed herein are innovations for bitstreams having clean random access (CRA) pictures and/or other types of random access point (RAP) pictures. New type definitions and strategic constraints on types of RAP pictures can simplify mapping of units of elementary video stream data to a container format. Such innovations can help improve the ability for video coding systems to more flexibly perform adaptive video delivery, production editing, commercial insertion, and the like.
CONSTRAINTS AND UNIT TYPES TO SIMPLIFY VIDEO RANDOM ACCESS
Granted: November 28, 2024
Application Number:
20240397100
Disclosed herein are innovations for bitstreams having clean random access (CRA) pictures and/or other types of random access point (RAP) pictures. New type definitions and strategic constraints on types of RAP pictures can simplify mapping of units of elementary video stream data to a container format. Such innovations can help improve the ability for video coding systems to more flexibly perform adaptive video delivery, production editing, commercial insertion, and the like.
CONSTRAINTS AND UNIT TYPES TO SIMPLIFY VIDEO RANDOM ACCESS
Granted: November 28, 2024
Application Number:
20240397099
Disclosed herein are innovations for bitstreams having clean random access (CRA) pictures and/or other types of random access point (RAP) pictures. New type definitions and strategic constraints on types of RAP pictures can simplify mapping of units of elementary video stream data to a container format. Such innovations can help improve the ability for video coding systems to more flexibly perform adaptive video delivery, production editing, commercial insertion, and the like.
CONSTRAINTS AND UNIT TYPES TO SIMPLIFY VIDEO RANDOM ACCESS
Granted: November 28, 2024
Application Number:
20240397098
Disclosed herein are innovations for bitstreams having clean random access (CRA) pictures and/or other types of random access point (RAP) pictures. New type definitions and strategic constraints on types of RAP pictures can simplify mapping of units of elementary video stream data to a container format. Such innovations can help improve the ability for video coding systems to more flexibly perform adaptive video delivery, production editing, commercial insertion, and the like.
CONSTRAINTS AND UNIT TYPES TO SIMPLIFY VIDEO RANDOM ACCESS
Granted: November 28, 2024
Application Number:
20240397097
Disclosed herein are innovations for bitstreams having clean random access (CRA) pictures and/or other types of random access point (RAP) pictures. New type definitions and strategic constraints on types of RAP pictures can simplify mapping of units of elementary video stream data to a container format. Such innovations can help improve the ability for video coding systems to more flexibly perform adaptive video delivery, production editing, commercial insertion, and the like.
COMPUTERIZED DEMANUFACTURING SYSTEM
Granted: November 28, 2024
Application Number:
20240391038
A method for automated device disassembly includes, at a computerized demanufacturing system, receiving a target electronic device for disassembly. Using a set of one or more sensors of the computerized demanufacturing system, a set of sensor data is collected that quantifies one or more physical properties of the target electronic device. Based at least in part on the set of sensor data, correspondences are identified between one or more effectors of the computerized demanufacturing…
CONSTRAINTS AND UNIT TYPES TO SIMPLIFY VIDEO RANDOM ACCESS
Granted: November 28, 2024
Application Number:
20240397095
Disclosed herein are innovations for bitstreams having clean random access (CRA) pictures and/or other types of random access point (RAP) pictures. New type definitions and strategic constraints on types of RAP pictures can simplify mapping of units of elementary video stream data to a container format. Such innovations can help improve the ability for video coding systems to more flexibly perform adaptive video delivery, production editing, commercial insertion, and the like.
FEATURES OF BASE COLOR INDEX MAP MODE FOR VIDEO AND IMAGE CODING AND DECODING
Granted: November 28, 2024
Application Number:
20240397089
Innovations in the use of base color index map (“BCIM”) mode during encoding and/or decoding simplify implementation by reducing the number of modifications made to support BCIM mode and/or improve coding efficiency of BCIM mode. For example, some of the innovations involve reuse of a syntax structure that is adapted for transform coefficients to instead signal data for elements of an index map in BCIM mode. Other innovations relate to mapping of index values in BCIM mode or…
Accelerating the Processing of a Stream of Media Data Using a Client Media Engine
Granted: November 28, 2024
Application Number:
20240397073
A technique processes a stream of media data in an accelerated manner using a media engine provided by a client system. The media engine performs this task, under direction of a local controller, using a pipeline of integrated inline media-processing operations having access to local memory. The operations include: decrypting received encrypted media data to produce decrypted media data; decoding the decrypted media data to produce decoded media data; and enhancing the decoded media data…
CONSTRAINTS ON LOCATIONS OF REFERENCE BLOCKS FOR INTRA BLOCK COPY PREDICTION
Granted: November 28, 2024
Application Number:
20240397061
When encoding/decoding a current block of a current picture using intra block copy (“BC”) prediction, the location of a reference block is constrained so that it can be entirely within an inner search area of the current picture or entirely within an outer search area of the current picture, but cannot overlap both the inner search area and the outer search area. In some hardware-based implementations, on-chip memory buffers sample values of the inner search area, and off-chip memory…
Constructing Prompt Information for Submission to a Language Model by Dynamically Selecting from Context Information
Granted: November 28, 2024
Application Number:
20240394477
A technique for interacting with a machine-trained language model uses dynamic prompt management. The technique includes: receiving an input query; accessing a state data store that provides candidate context information; partitioning the candidate context information into plural parts; selecting targeted context information from the candidate context information by determining a semantic relevance of the input query to each of the plural parts by performing vector-based analysis;…
Solving Differential Equations with Deep Learning
Granted: November 28, 2024
Application Number:
20240394330
This document relates to solving challenges associated with solving partial differential equations (PDEs) via numerical simulations relating to natural or physical systems. One example obtains input data relating to a physical system and partitions tensors of a neural network across multiple parallel processors. The example distributes the input data across multiple parallel cloud processing resources for numerical simulations involving partial differential equations to produce…
MATERIALS INFORMATION DATABASE INCLUDING MACHINE LEARNING MODELS
Granted: November 28, 2024
Application Number:
20240394258
Examples are disclosed that relate to materials discovery using machine learning models. One example provides a method enacted on a computing system. The method comprises receiving a query comprising one or more of element information and material property information, and, based on the query, retrieving material data from a materials information database. The material data comprises structural information for each material within a set of materials matching the query, the set comprising…
UPDATING A CLOUD SERVICE WITH FARMS GROUPED FOR A SAME UPDATE DEPLOYMENT STAGE
Granted: November 28, 2024
Application Number:
20240394035
An orchestrator for updating a cloud service includes: an orchestrator service host computer comprising a processor and memory; an orchestrator service for execution by the orchestrator service host computer for orchestrating updates to farms of the cloud service over a service bus; a stage management service for determining which farms should be in each stage of an update deployed by the orchestrator service; and a grouping table identifying farms that should be in a common stage of the…
PREDICTIVE SCREEN RECORDING
Granted: November 28, 2024
Application Number:
20240393913
Aspects of the present disclosure relate to predictive screen recording. In examples, a user initiates screen recording, such that an initial recording region is recorded. During screen recording, one or more events, user inputs, and/or any of a variety of other features are processed to generate a predicted recording region, which is used to update the region for which screen recording output is generated accordingly. Thus, the recorded region of the screen may change dynamically,…
