公开(公告)号：US20240244172A1

公开(公告)日：2024-07-18

申请号：US18275596

申请日：2021-03-18

Applicant: Intel Corporation

Inventor： Ying Luo ,  Hua Zhang ,  Xiaomin Chen ,  Xin Kang

IPC: H04N13/117 ,  H04N13/194 ,  H04N13/332 ,  H04N13/366 ,  H04N21/81

CPC classification number: H04N13/117 ,  H04N13/194 ,  H04N13/332 ,  H04N13/366 ,  H04N21/816

Abstract: Techniques related to viewport selection in immersive video contexts are discussed. Such techniques include generating multiple viewport predictions each for a future time interval and based on different prediction models, ranking the viewport predictions using error descriptors of the prediction models, selecting a viewport prediction for the future time intervals using the ranking, and correcting the selected viewport predictions using the error descriptors.

公开(公告)号：US20210116982A1

公开(公告)日：2021-04-22

申请号：US17133226

申请日：2020-12-23

Applicant: Intel Corporation

Inventor： Rahul Khanna ,  Xin Kang ,  Ali Taha ,  James Tschanz ,  William Zand ,  Robert Kwasnick

IPC: G06F1/324 ,  G06F1/3296 ,  G06F1/3287 ,  G06F9/50

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to optimize a guard band of a hardware resource. An example apparatus includes at least one storage device, and at least one processor to execute instructions to identify a phase of a workload based on an output from a machine-learning model, the phase based on a utilization of one or more hardware resources, and based on the phase, control a guard band of a first hardware resource of the one or more hardware resources.

公开(公告)号：US12130688B2

公开(公告)日：2024-10-29

申请号：US17133226

申请日：2020-12-23

Applicant: Intel Corporation

Inventor： Rahul Khanna ,  Xin Kang ,  Ali Taha ,  James Tschanz ,  William Zand ,  Robert Kwasnick

IPC: G06F1/324 ,  G06F1/3287 ,  G06F1/3296 ,  G06F9/50

CPC classification number: G06F1/324 ,  G06F1/3287 ,  G06F1/3296 ,  G06F9/5094

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to optimize a guard band of a hardware resource. An example apparatus includes at least one storage device, and at least one processor to execute instructions to identify a phase of a workload based on an output from a machine-learning model, the phase based on a utilization of one or more hardware resources, and based on the phase, control a guard band of a first hardware resource of the one or more hardware resources.