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公开(公告)号:US12069172B2
公开(公告)日:2024-08-20
申请号:US17452496
申请日:2021-10-27
Inventor: Bo Jing , Peiqian Zhang , Hongyan Wang
CPC classification number: H04L9/088 , H04L9/3247
Abstract: Provided are a group service implementation method and device, an equipment and a storage medium. The specific solution is described below. A service transaction request is acquired. In response to the service transaction request including to-be-authenticated data and a threshold signature, a signature group corresponding to the threshold signature is determined. Group information of the signature group is acquired by querying a blockchain, where the signature group includes at least two members, the at least two members of the signature group are used for authenticating the to-be-authenticated data by adopting secure multi-party computation and generating the threshold signature for the to-be-authenticated data by adopting a signature private key, and the group information includes at least a verification public key of the threshold signature. The threshold signature is verified by adopting the verification public key in the group information.
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公开(公告)号:US12067067B2
公开(公告)日:2024-08-20
申请号:US17850930
申请日:2022-06-27
Inventor: JuanJuan Shui , Yingjie Niu , Qiushen Qu , Weipeng Niu , Jiankang Xin
IPC: G06F16/9537 , G06F16/9535 , G06F16/9538
CPC classification number: G06F16/9537 , G06F16/9535 , G06F16/9538
Abstract: A site recommendation method, an electronic device, and a readable storage medium are provided, which relate to the field of automatic driving. The method includes: determining, in response to a query request of a user terminal for a target position, a target site recommended to a target user within a specified range of the target position, wherein the target site includes a site that the target user is interested in under a specified travel condition; and sending the target site to the user terminal.
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公开(公告)号:US20240275848A1
公开(公告)日:2024-08-15
申请号:US18020618
申请日:2022-08-01
Inventor: Guoxia WANG , Long LI , Zhihua WU
IPC: H04L67/1097 , G06F7/58
CPC classification number: H04L67/1097 , G06F7/582 , G06F7/588
Abstract: The present disclosure provides a content initialization method and apparatus, an electronic device and a storage medium, which relates to a field of computer technology, in particular to fields of deep learning and distributed computing. The content initialization method is applied to any one of a plurality of devices included in a distributed system. A specific implementation scheme of the content initialization method is: determining, according to a size information of a resource space for the distributed system and an identification information of the any one of the plurality of devices, a space information of a first sub-space for the any one of the plurality of devices in the resource space, wherein the space information includes a position information of the first sub-space for the resource space; and determining an initialization content for the first sub-space according to a random seed and the position information.
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公开(公告)号:US12039967B2
公开(公告)日:2024-07-16
申请号:US17520799
申请日:2021-11-08
Inventor: Yanyan Li , Dejing Dou
CPC classification number: G10L15/01 , G10L15/02 , G10L15/063 , G10L15/22 , G10L2015/225
Abstract: A method for evaluating satisfaction with voice interaction, a device, and a storage medium are provided, which are related to a technical field of artificial intelligence, in particular, to fields of natural language processing, knowledge graph and deep learning, and can be applied to user intention understanding. The specific implementation includes: acquiring sample interaction data of a plurality of rounds of sample voice interaction behaviors; performing feature extractions on respective sample interaction data, to obtain a sample interaction feature sequence; acquiring satisfaction marks corresponding to the respective sample interaction data, to obtain a satisfaction mark sequence; and training an initial model by using a plurality of sets of sample interaction feature sequences and of satisfaction mark sequences, to obtain the model for evaluating satisfaction.
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345.
公开(公告)号:US20240231840A1
公开(公告)日:2024-07-11
申请号:US17914893
申请日:2021-10-14
Inventor: Chao LIU
IPC: G06F9/445
CPC classification number: G06F9/44505
Abstract: Provided are a method and apparatus for microservice configuration, an electronic device, a system and a storage medium in the present disclosure, relates to the field of computer technologies, and in particular to the field of cloud computing, Internet of things, etc. A specific implementation solution is as follows. Configuration data is received from a main cluster; a service data acquisition request is sent to the main cluster in response to determining that service data in the main cluster has been changed, and the changed service data is received from the main cluster; and at least one service governance task is executed according to the configuration data and the changed service data.
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公开(公告)号:US12034820B2
公开(公告)日:2024-07-09
申请号:US17676056
申请日:2022-02-18
IPC: H04L41/042 , G06F11/07 , H04L41/16 , H04L43/12 , H04L67/51
CPC classification number: H04L67/51 , G06F11/076 , H04L43/12
Abstract: Provided are a fusing and degradation method and apparatus for a micro-service, a device, a medium, and a program product, which relate to the field of the Internet, in particular to the field of fusing and degradation. The specific implementation is as follows: instantiating, by a monitoring probe woven into a micro-service traffic process, a fuse component according to an obtained fusing and degradation rule, and weaving, by the monitoring probe, the fuse component into the traffic process, where the fuse component is used for performing fusing and degradation on a traffic request processed in the traffic process. The fusing and degradation technology during the running of a micro-service is achieved through a probe so that the micro-service developer can fuse and degrade a micro-service application that is running without hard coding, thereby improving the efficiency and stability of the micro-service fusing and degradation.
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347.
公开(公告)号:US20240221346A1
公开(公告)日:2024-07-04
申请号:US17800880
申请日:2022-01-29
Inventor: Zhigang WANG , Jian WANG , Hao SUN , Errui DING
IPC: G06V10/44 , G06T9/00 , G06V10/74 , G06V10/762 , G06V10/80
CPC classification number: G06V10/44 , G06T9/00 , G06V10/761 , G06V10/762 , G06V10/806
Abstract: The present disclosure provides a model training method and apparatus, a pedestrian re-identification method and apparatus, and an electronic device, and relates to the field of artificial intelligence, and specifically to computer vision and deep learning technologies, which can be applied to smart city scenarios. A specific implementation solution is: performing, by using a first encoder, feature extraction on a first pedestrian image and a second pedestrian image in a sample dataset, to obtain an image feature of the first pedestrian image and an image feature of the second pedestrian image; fusing the image feature of the first pedestrian image and the image feature of the second pedestrian image, to obtain a fused feature; performing, by using a first decoder, feature decoding on the fused feature, to obtain a third pedestrian image; and determining the third pedestrian image as a negative sample image of the first pedestrian image, and using the first pedestrian image and the negative sample image to train a first preset model to convergence, to obtain a pedestrian re-identification model. The embodiments of the present disclosure can improve the effect of the model in distinguishing between pedestrians with similar appearances but different identities.
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348.
公开(公告)号:US20240193923A1
公开(公告)日:2024-06-13
申请号:US17908070
申请日:2022-01-29
Inventor: Xiaodi WANG , Shumin HAN , Yuan FENG , Ying XIN , Yi GU , Bin ZHANG , Chao LI , Xiang LONG , Honghui ZHENG , Yan PENG , Zhuang JIA , Yunhao WANG
IPC: G06V10/778
CPC classification number: G06V10/778 , G06V2201/07
Abstract: A method of training a target object detection model includes: extracting a plurality of feature maps of a sample image according to a training parameter, fusing the plurality of feature maps to obtain at least one fused feature map, and obtaining an information of a target object based on the at least one fused feature map, by using the target object detection model; determining a loss of the target object detection model based on the information of the target object and a tag information of the sample image, and adjusting the training parameter according to the loss of the target object detection model. A method of detecting a target object and an apparatus are also provided.
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公开(公告)号:US12007965B2
公开(公告)日:2024-06-11
申请号:US17663044
申请日:2022-05-12
Inventor: Yifei Wang , Yang Wang , Yu Wang
IPC: G06F16/215 , G06F16/901
CPC classification number: G06F16/215 , G06F16/9014 , G06F16/9024
Abstract: The disclosure provides a method for deduplicating entity nodes in a graph database. The method includes: obtaining a set of entity nodes to be deduplicated from the knowledge graph, in which the set includes a plurality of entity nodes; selecting an untraversed entity node from the set as a target entity node; determining a range located by a node identifier corresponding to the target entity node; determining the target entity node that has appeared in traversed entity nodes according to a deduplicating mode corresponding to the range; and deleting the target entity node from the set.
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350.
公开(公告)号:US20240177469A1
公开(公告)日:2024-05-30
申请号:US17793999
申请日:2021-11-17
Inventor: Miao FAN , Jizhou HUANG , Haifeng WANG
IPC: G06V10/82 , G06V10/771 , G06V10/80
CPC classification number: G06V10/82 , G06V10/771 , G06V10/80
Abstract: A method and apparatus for encoding a geographic location region as well as a method and apparatus for establishing an encoding model, which relate to big data and deep learning technologies in the field of artificial intelligence technologies are disclosed. An implementation includes: determining a to-be-encoded geographic location region; acquiring at least one kind of geographic function information and at least one kind of surface-feature distribution information of the geographic location region; and inputting the acquired geographic function information and the acquired surface-feature distribution information into an encoding model, the encoding model performing embedding on the geographic function information and the surface-feature distribution information, and fusing vector representations obtained by the embedding to obtain an encoding result of the geographic location region.
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