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公开(公告)号:US20230207120A1
公开(公告)日:2023-06-29
申请号:US18177059
申请日:2023-03-01
Applicant: Huawei Technologies Co., Ltd.
Inventor: Jialing Wu , Jian Li , Han Su , Yingxuan Zhu
IPC: G16H40/67 , G16H40/40 , G06N3/0442
CPC classification number: G16H40/67 , G16H40/40 , G06N3/0442
Abstract: A method implemented by an agent monitoring device, comprises obtaining, by a sensor of the agent monitoring device, sensor data over a period of time, the sensor data describing a characteristic of an agent associated with the agent monitoring device, determining output data for the sensor based on the sensor data using a learning model, determining a sensor condition for the sensor, determining that a power level of a battery of the agent monitoring device meets the pre-defined power level, determining whether the output data meets the threshold value of the sensor condition in response to the power level of the battery having reached the pre-defined power level, and uploading an indication of the output data to at least one of a cloud server or a representative device in response to the output data for the sensor having met the threshold value of the sensor condition.
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公开(公告)号:US20230267569A1
公开(公告)日:2023-08-24
申请号:US18306437
申请日:2023-04-25
Applicant: Huawei Technologies Co., Ltd.
Inventor: Yingxuan Zhu , Yong Wang , Theodoros Gkountouvas , Han Su , Hui Lei
CPC classification number: G06T1/20 , G06F9/5027 , G06F9/4881
Abstract: The disclosure relates to technology for acceleration of GPUs in cloud. Instructions for a computational task are accessed. An allocation of data and instructions is calculated based on the data, the instructions, and dynamic GPU resources. The data and the instructions are provided to the GPUs in accordance with the allocation, which includes scheduling a set of instructions for parallel computation of an operation of the computational task on multiple sub-matrices of a data matrix. Separate portions of information are stored into corresponding different regions of non-transitory memory of a processor core to provide concurrent access to the multiple sub-matrices to the processor core. Each sub-matrix corresponds to a portion of the data matrix for which an operation of the computational task is to be performed. Each sub-matrix contains an element in the data matrix in common with another sub-matrix of the data matrix.
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3.
公开(公告)号:US20210341886A1
公开(公告)日:2021-11-04
申请号:US17319442
申请日:2021-05-13
Applicant: Huawei Technologies Co., Ltd.
Inventor: Lifeng Liu , Yingxuan Zhu , Jun Zhang , Xiaofian Yin , Jian Li , Yongxiang Tao , Dayao Liang
IPC: G05B13/02 , G06F16/2457 , B60W50/06
Abstract: A computer implemented method for self-learning of a control system. The method includes creating an initial knowledge base. The method learns first principles using the knowledge base. The method creates initial control commands derived from the knowledge base. The method generates constraints for the control commands. The method performs constrained reinforcement learning by executing the control commands with the constraints and observing feedback to improve the control commands. The method enriches the knowledge base based on the feedback.
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公开(公告)号:US20250028047A1
公开(公告)日:2025-01-23
申请号:US18585862
申请日:2024-02-23
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor: Yingxuan Zhu
IPC: G01S17/46 , B60W30/09 , B60W30/095 , G01S7/48 , G01S17/89 , G01S17/931
Abstract: A method of detecting hidden objects in a dynamic environment of a main object. In an embodiment, the method is implemented by a main object. The main object selects a surface object in the dynamic environment to reflect a light signal. The main object transmits a light signal from the main object to the surface object to obtain data based on a reflection of the light signal off the surface object. The main object analyzes the data to detect a hidden object that is not directly in the line of sight of the main object.
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5.
公开(公告)号:US12189349B2
公开(公告)日:2025-01-07
申请号:US17319442
申请日:2021-05-13
Applicant: Huawei Technologies Co., Ltd.
Inventor: Lifeng Liu , Yingxuan Zhu , Jun Zhang , Xiaotian Yin , Jian Li , Yongxiang Tao , Dayao Liang
IPC: G05B13/02 , B60W50/06 , B60W60/00 , G06F16/2457 , B60W50/00
Abstract: A computer implemented method for self-learning of a control system. The method includes creating an initial knowledge base. The method learns first principles using the knowledge base. The method creates initial control commands derived from the knowledge base. The method generates constraints for the control commands. The method performs constrained reinforcement learning by executing the control commands with the constraints and observing feedback to improve the control commands. The method enriches the knowledge base based on the feedback.
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公开(公告)号:US11899837B2
公开(公告)日:2024-02-13
申请号:US17716438
申请日:2022-04-08
Applicant: Huawei Technologies Co., Ltd.
Inventor: Yingxuan Zhu , Wenyou Sun , Jian Li
CPC classification number: G06F3/013 , G06F3/14 , G06T7/68 , G06V10/143 , G06V10/42 , G06V40/161 , G06V40/172 , G06V40/19 , G06V40/193 , G06T2207/10028
Abstract: The disclosure relates to technology for detecting and tracking eye gaze. An apparatus comprises a visible wavelength camera, an infrared (IR) camera, and one or more processors. The one or more processors are configured to generate a three-dimensional (3D) point cloud of a person's face from IR data captured from the IR camera, generate a two-dimensional image of the person's face from visible wavelength data captured from the visible wavelength camera, and detect a symmetry plane of the person's face based on the 3D point cloud and the two-dimensional image. The symmetry plane divides the 3D point cloud into two portions. The one or more processors are further configured to reconstruct the 3D point cloud based on the symmetry plane, and track eye gaze of the person's face based on the reconstructed 3D point cloud.
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公开(公告)号:US20230385652A1
公开(公告)日:2023-11-30
申请号:US18336895
申请日:2023-06-16
Applicant: Huawei Technologies Co., Ltd.
Inventor: Yingxuan Zhu , Jialing Wu , Han Su
IPC: G06N3/098
CPC classification number: G06N3/098
Abstract: The present technology discloses a federated learning network including a server and multiple client devices. The server receives a set of parameters of a local machine-learning model from each client device in a subset of the multiple client devices. The set of parameters are combined from each of the client devices in the subset to generate an integrated set of parameters. The server then calculates a parameter difference between the integrated set of parameters and the set of parameters for each client device in the subset. Feedback is sent by the server to each client device in the subset. The feedback is applied during backpropagation of the client. If the local parameters of a client are determined to be invalid for a number of times, the client will be set as an outlier.
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公开(公告)号:US20220229492A1
公开(公告)日:2022-07-21
申请号:US17716438
申请日:2022-04-08
Applicant: Huawei Technologies Co., Ltd.
Inventor: Yingxuan Zhu , Wenyou Sun , Jian Li
Abstract: The disclosure relates to technology for detecting and tracking eye gaze. An apparatus comprises a visible wavelength camera, an infrared (IR) camera, and one or more processors. The one or more processors are configured to generate a three-dimensional (3D) point cloud of a person's face from IR data captured from the IR camera, generate a two-dimensional image of the person's face from visible wavelength data captured from the visible wavelength camera, and detect a symmetry plane of the person's face based on the 3D point cloud and the two-dimensional image. The symmetry plane divides the 3D point cloud into two portions. The one or more processors are further configured to reconstruct the 3D point cloud based on the symmetry plane, and track eye gaze of the person's face based on the reconstructed 3D point cloud.
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9.
公开(公告)号:US20220155732A9
公开(公告)日:2022-05-19
申请号:US17319442
申请日:2021-05-13
Applicant: Huawei Technologies Co., Ltd.
Inventor: Lifeng Liu , Yingxuan Zhu , Jun Zhang , Xiaotian Yin , Jian Li , Yongxiang Tao , Dayao Liang
IPC: G05B13/02 , G06F16/2457 , B60W50/06
Abstract: A computer implemented method for self-learning of a control system. The method includes creating an initial knowledge base. The method learns first principles using the knowledge base. The method creates initial control commands derived from the knowledge base. The method generates constraints for the control commands. The method performs constrained reinforcement learning by executing the control commands with the constraints and observing feedback to improve the control commands. The method enriches the knowledge base based on the feedback.
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