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公开(公告)号：US20210004625A1
公开(公告)日：2021-01-07
申请号：US17025419
申请日：2020-09-18
Applicant: Huawei Technologies Co., Ltd.
Inventor： Changzheng Zhang , Xin Jin , Dandan Tu
Abstract: In an object detection model training method, a classifier that has been trained in a first phase is duplicated to at least two copies, and in a training in a second phase, each classifier obtained through duplication is configured to detect to-be-detected objects with different sizes, and train an object detection model based on a detection result.
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公开(公告)号：US20220172476A1
公开(公告)日：2022-06-02
申请号：US17568705
申请日：2022-01-04
Applicant: HUAWEI TECHNOLOGIES CO.,LTD.
Inventor： Jun Li , Haomiao Liu , Weimeng Gong , Dandan Tu
Abstract: A video similarity detection method and apparatus are provided. In the method, a detection apparatus receives a first video, determines a key frame of the first video based on the first video, and determines a similar key frame and a second video, the similar key frame being determined based on the key frame. The second video includes a video in which the similar key frame is located. The method inputs the key frame and the similar key frame to an editing type recognition model to obtain an editing type. The editing type indicates an editing type used for editing between the first video and the second video.
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公开(公告)号：US10764125B2
公开(公告)日：2020-09-01
申请号：US16044757
申请日：2018-07-25
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Youhua Zhang , Dandan Tu
IPC: G06F15/177 , H04L12/24 , G06N20/00 , G06F9/50 , H04L29/08
Abstract: A method and a device for training a model in a distributed system are disclosed, so as to reduce load of a master node (101) during model training. The method includes: receiving, by a parameter server (1022) in a first slave node (102), a training result sent by a parameter client (1021) in at least one slave node (102) in the distributed system, where the first slave node (102) is any slave node (102) in the distributed system, and a parameter client (1021) in each slave node (102) obtains a training result by executing a training task corresponding to a sub-model stored on a parameter server (1022) in the slave node (102); and updating, by the parameter server (1022) in the first slave node (102) based on the received training result, a sub-model stored on the parameter server in the first slave node.
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公开(公告)号：US11461659B2
公开(公告)日：2022-10-04
申请号：US15871460
申请日：2018-01-15
Applicant: Huawei Technologies Co., Ltd.
Inventor： Dandan Tu , Jiajin Zhang
Abstract: A feature set determining method includes obtaining, according to a received feature set determining request, data used for feature learning. The feature set determining request includes a learning objective of the feature learning. The method includes performing type analysis on the data to divide the data into first-type data and second-type data. The method includes performing semi-supervised learning on the first-type data to extract multiple first-type features. The method includes performing adaptive learning on the second-type data to extract multiple second-type features. The method includes evaluating the first-type features and the second-type features to obtain an optimal feature set.
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公开(公告)号：US11182080B2
公开(公告)日：2021-11-23
申请号：US15960292
申请日：2018-04-23
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Shiyue Zhuang , Yulei Xiao , Dandan Tu
IPC: G06F3/06 , G06F16/182 , G06F16/00 , G06F11/10
Abstract: An adaptive file storage method and apparatus is disclosed. The method includes determining a cold and hot attribute of a file, and performing coding storage processing or transcoding storage processing on the file according to the cold and hot attribute of the file. Therefore, a requirement of the cold and hot attribute of the file for storage overheads and restoration costs can be fully considered. In addition, the used coding technology has high reliability and a high coding speed. Therefore, comprehensive performance in multiple dimensions of storage overheads, restoration costs, reliability, and an coding speed can be improved.
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Patent Agency Ranking
公开(公告)号：US20210012136A1
公开(公告)日：2021-01-14
申请号：US17036903
申请日：2020-09-29
Applicant: Huawei Technologies Co., Ltd.
Inventor： Changzheng Zhang , Xin Jin , Dandan Tu
Abstract: An object detection model training method performed by a computing device, includes obtaining a system parameter including at least one of a receptive field of a backbone network, a size of a training image, a size of a to-be-detected object in the training image, a training computing capability, or a complexity of the to-be-detected object, determining a configuration parameter based on the system parameter, establishing a variable convolution network based on the configuration parameter and a feature map of the backbone network, recognizing the to-be-detected object based on a feature of the variable convolution network, and training the backbone network and the variable convolution network, where a convolution core used by any variable convolution layer may be offset in any direction in a process of performing convolution.
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7.发明授权公开(公告)号：US10437816B2
公开(公告)日：2019-10-08
申请号：US15264294
申请日：2016-09-13
Applicant: Huawei Technologies Co., Ltd.
Inventor： Yong Zhang , Bian Yin , Dandan Tu
Abstract: A method and an apparatus for reconstructing a cube in a multidimensional online analytical processing (MOLAP) system, where a cube is reconstructed based on a received reconstruction request and data stored in an old cube, and there is no need to acquire, from a database, data required for updating the cube, thereby ensuring data integrity when model reconstruction and data reconstruction are performed in the MOLAP system.
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公开(公告)号：US20180150746A1
公开(公告)日：2018-05-31
申请号：US15871460
申请日：2018-01-15
Applicant: Huawei Technologies Co., Ltd.
Inventor： Dandan Tu , Jiajin Zhang
CPC classification number: G06N3/088 , G06F17/16 , G06K9/00221 , G06K9/4628 , G06K9/6234 , G06K9/6271 , G06N3/0454
Abstract: A feature set determining method includes obtaining, according to a received feature set determining request, data used for feature learning. The feature set determining request includes a learning objective of the feature learning. The method includes performing type analysis on the data to divide the data into first-type data and second-type data. The method includes performing semi-supervised learning on the first-type data to extract multiple first-type features. The method includes performing adaptive learning on the second-type data to extract multiple second-type features. The method includes evaluating the first-type features and the second-type features to obtain an optimal feature set.
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公开(公告)号：US20170091805A1
公开(公告)日：2017-03-30
申请号：US15378311
申请日：2016-12-14
Applicant: Huawei Technologies Co., Ltd.
Inventor： Dandan Tu , Yong Zhang
IPC: G06Q30/02
CPC classification number: G06Q30/0244 , G06Q30/0255 , G06Q30/0277
Abstract: An advertisement recommendation method and an advertisement recommendation server. The method includes: acquiring webpage visit information and advertisement click information; predicting, according to the webpage visit information and the advertisement click information, probabilities of clicking x advertisements when the ith user among m users visits the jth webpage; determining a novelty factor corresponding to each respective advertisement of the x advertisements; and determining, from the x advertisements according to the probabilities of clicking the x advertisements and the novelty factor corresponding to the respective advertisement, p advertisements to be recommended to the ith user.
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10.发明申请Method And Apparatus For Reconstructing Cube In Multidimensional Online Analytical Processing System 审中-公开用于在多维在线分析处理系统中重建立方体的方法和装置公开(公告)号：US20170004170A1
公开(公告)日：2017-01-05
申请号：US15264294
申请日：2016-09-13
Applicant: Huawei Technologies Co., Ltd.
Inventor： Yong Zhang , Bian Yin , Dandan Tu
IPC: G06F17/30
CPC classification number: G06F16/2365 , G06F16/27 , G06F16/283
Abstract: A method and an apparatus for reconstructing a cube in a multidimensional online analytical processing (MOLAP) system, where a cube is reconstructed based on a received reconstruction request and data stored in an old cube, and there is no need to acquire, from a database, data required for updating the cube, thereby ensuring data integrity when model reconstruction and data reconstruction are performed in the MOLAP system.
Abstract translation: 一种用于在多维在线分析处理（MOLAP）系统中重建立方体的方法和装置，其中基于接收到的重建请求和存储在旧立方体中的数据重建多维数据集，并且不需要从数据库中获取 ，更新多维数据集所需的数据，从而确保在MOLAP系统中执行模型重建和数据重建时的数据完整性。
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