公开(公告)号：US20210271923A1

公开(公告)日：2021-09-02

申请号：US17255331

申请日：2018-09-07

Applicant: Intel Corporation

Inventor： Kun Yu ,  Ciyong Chen ,  Xiaotian Guo ,  Yan Hao ,  Hui Li ,  Lu Li ,  Jianguo Pei ,  Zhi Yong Zhu

IPC: G06K9/62 ,  G06K9/32 ,  G06K9/00 ,  G06K9/46 ,  G06N3/04

Abstract: An example apparatus for detecting objects in video frames includes a receiver to receive a plurality of video frames from a video camera. The apparatus also includes a first still image object detector to receive a first frame of the plurality of video frames and calculate localization information and confidence information for each potential object patch in the first frame. The apparatus further includes a second still image object detector to receive an adjacent frame of the plurality of video frames adjacent to the first frame and calculate localization information and confidence information for each potential object patch in the adjacent frame. The apparatus includes a similarity detector trained to detect paired patches between the first frame and the adjacent frame based on a comparison of the detected potential object patches. The apparatus further includes an enhancer to modify a prediction result for a paired patch in the adjacent frame to a prediction result of a corresponding paired patch in the first frame including a higher confidence score than the prediction result of the paired patch in the adjacent frame.

公开(公告)号：US20180174349A1

公开(公告)日：2018-06-21

申请号：US15118887

申请日：2014-06-30

Applicant: INTEL CORPORATION

Inventor： Yi Yang ,  Xiaoming Chen ,  Feng Chen ,  Yan Hao

IPC: G06T15/00 ,  G06T15/04 ,  G06T1/60 ,  G06T11/40

CPC classification number: G06T15/005 ,  G06T1/60 ,  G06T11/40 ,  G06T15/04 ,  G06T2200/04

Abstract: Methods and apparatus relating to an adaptive partition mechanism with arbitrary tile shape for tile based rendering GPU (Graphics Processing Unit) architecture are described. In an embodiment, the primitive intersection cost value for each atomic tile of an image are determined at least partially based on a vertex element size, a vertex shader length, and a number of the vertices of a primitive of the image. Other embodiments are also disclosed and claimed.

公开(公告)号：US20150220371A1

公开(公告)日：2015-08-06

申请号：US14128563

申请日：2013-03-04

Applicant: Rongzhen YANG ,  Hujun YIN ,  Feng CHEN ,  Johnson Z. WU ,  Yan Mars HAO ,  Yi YANG ,  INTEL CORPORATION

Inventor： Rongzhen Yang ,  Hujun Yin ,  Feng Chen ,  Johnson Z. Wu ,  Yan Hao ,  Yi Yang

IPC: G06F9/50 ,  G06F9/48

CPC classification number: G06F9/5094 ,  G06F9/4893 ,  Y02D10/22

Abstract: An energy aware framework for computation and communication devices (CCDs) is disclosed. CCDs may support applications, which may participate in energy aware optimization. Such applications may be designed to support execution modes, which may be associated with different computation and communication demands or requirements. An optimization block may collect computation requirement values (CRVM), communication demand values (CDVM), and such other values of each execution mode to perform a specific task(s). The optimization block may collect computation energy cost information (CECIM) and multi-radio communication energy cost information (MCECIM) for each execution mode. Also, the optimization block may collect the workload values of a cloud-side processing device. The optimization block may determine power estimation values (PEV), based on the energy cost values (CECIM), (MCECIM), CRVM, and CDVM. The optimization block may then determine the execution mode or the apparatus best suited to perform the tasks.

Abstract translation: 公开了一种用于计算和通信设备（CCD）的能量感知框架。 CCD可以支持可能参与能量感知优化的应用。 这样的应用可以被设计为支持可能与不同计算和通信需求或需求相关联的执行模式。 优化块可以收集计算需求值（CRVM），通信需求值（CDVM）以及每个执行模式的其他值以执行特定的任务。 优化块可以针对每个执行模式收集计算能量成本信息（CECIM）和多无线电通信能量成本信息（MCECIM）。 此外，优化块可以收集云端处理设备的工作负载值。 优化块可以基于能量成本值（CECIM），（MCECIM），CRVM和CDVM来确定功率估计值（PEV）。 然后，优化块可以确定执行模式或者最适于执行任务的装置。

公开(公告)号：US11948340B2

公开(公告)日：2024-04-02

申请号：US17255331

申请日：2018-09-07

Applicant: Intel Corporation

Inventor： Kun Yu ,  Ciyong Chen ,  Xiaotian Guo ,  Yan Hao ,  Hui Li ,  Lu Li ,  Jianguo Pei ,  Zhi Yong Zhu

IPC: G06V10/25 ,  G06F18/21 ,  G06F18/22 ,  G06N3/045 ,  G06V10/62 ,  G06V10/74 ,  G06V10/82 ,  G06V20/40 ,  G06V20/52

CPC classification number: G06V10/25 ,  G06F18/21 ,  G06F18/22 ,  G06N3/045 ,  G06V10/62 ,  G06V10/761 ,  G06V10/82 ,  G06V20/46 ,  G06V20/48 ,  G06V20/52

Abstract: An example apparatus for detecting objects in video frames includes a receiver to receive a plurality of video frames from a video camera. The apparatus also includes a first still image object detector to receive a first frame of the plurality of video frames and calculate localization information and confidence information for each potential object patch in the first frame. The apparatus further includes a second still image object detector to receive an adjacent frame of the plurality of video frames adjacent to the first frame and calculate localization information and confidence information for each potential object patch in the adjacent frame. The apparatus includes a similarity detector trained to detect paired patches between the first frame and the adjacent frame based on a comparison of the detected potential object patches. The apparatus further includes an enhancer to modify a prediction result for a paired patch in the adjacent frame to a prediction result of a corresponding paired patch in the first frame including a higher confidence score than the prediction result of the paired patch in the adjacent frame.

公开(公告)号：US11776263B2

公开(公告)日：2023-10-03

申请号：US17742122

申请日：2022-05-11

Applicant: Intel Corporation

Inventor： Yan Hao ,  Zhi Yong Zhu ,  Lu Li ,  Ciyong Chen ,  Kun Yu

IPC: G06K9/00 ,  G06V20/40 ,  G06F18/22 ,  G06F18/213 ,  G06V10/74 ,  G06V10/764 ,  G06V10/776 ,  G06V10/82

CPC classification number: G06V20/41 ,  G06F18/213 ,  G06F18/22 ,  G06V10/761 ,  G06V10/764 ,  G06V10/776 ,  G06V10/82 ,  G06V20/46

Abstract: Techniques related to training and implementing a bidirectional pairing architecture for object detection are discussed. Such techniques include generating a first enhanced feature map for each frame of a video sequence by processing the frames in a first direction, generating a second enhanced feature map for frame by processing the frames in a second direction opposite the first, and determining object detection information for each frame using the first and second enhanced feature map for the frame.

公开(公告)号：US11380086B2

公开(公告)日：2022-07-05

申请号：US16828987

申请日：2020-03-25

Applicant: Intel Corporation

Inventor： Kun Yu ,  Yan Hao ,  Lu Li ,  Zhiyong Zhu

IPC: G06V10/75 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08 ,  G06V10/22

Abstract: System and techniques are provided for three-dimension (3D) semantic segmentation. A device for 3D semantic segmentation includes: an interface, to obtain a point cloud data set for a time-ordered sequence of 3D frames, the 3D frames including a current 3D frame and one or more historical 3D frames previous to the current 3D frame; and processing circuitry, to: invoke a first artificial neural network (ANN) to estimate a 3D scene flow field for each of the one or more historical 3D frames by taking the current 3D frame as a reference frame; and invoke a second ANN to: produce an aggregated feature map, based on the reference frame and the estimated 3D scene flow field for each of the one or more historical 3D frames; and perform the 3D semantic segmentation based on the aggregated feature map.

公开(公告)号：US20220147837A1

公开(公告)日：2022-05-12

申请号：US17587407

申请日：2022-01-28

Applicant: Intel Corporation

Inventor： Feng Chen ,  Yan Hao ,  Yi Yang ,  Xiaoming Chen

IPC: G06N5/02 ,  G06N20/00 ,  G06F16/2458 ,  G06F21/00 ,  G06F16/903 ,  G06Q20/12 ,  G06F16/9535 ,  G06Q20/40

Abstract: A disclosed example includes selecting, by a mobile computing device, a model description for a predictive analytics model in response to a user-level application request including input data from an application of the mobile computing device, the model description created with a predictive analytics model description language, the model description received from a predictive analytics provider; comparing, by the mobile computing device, first data associated with the user-level application request with second data indicative of digital rights permissions associated with the model description; and executing, by the mobile computing device, an executable associated with the model description without providing the processor circuitry access to the executable and without providing the input data to the predictive analytics provider.

公开(公告)号：US11354903B2

公开(公告)日：2022-06-07

申请号：US17059968

申请日：2018-12-18

Applicant: Intel Corporation

Inventor： Yan Hao ,  Zhi Yong Zhu ,  Lu Li ,  Ciyong Chen ,  Kun Yu

IPC: G06K9/00 ,  G06V20/40 ,  G06K9/62

Abstract: Techniques related to training and implementing a bidirectional pairing architecture for object detection are discussed. Such techniques include generating a first enhanced feature map for each frame of a video sequence by processing the frames in a first direction, generating a second enhanced feature map for frame by processing the frames in a second direction opposite the first, and determining object detection information for each frame using the first and second enhanced feature map for the frame.