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公开(公告)号：US12056582B2
公开(公告)日：2024-08-06
申请号：US16921207
申请日：2020-07-06
Inventor： Bing Ren , Shengwen Yang , Xuhui Zhou
CPC classification number: G06N20/00 , G06F21/602 , H04L9/008 , H04L9/0825 , H04L9/3073 , G06F2221/2107
Abstract: A method and device for training a model based on federated learning are provided. The method includes: receiving a second original independent variable calculated value from a second data provider device; the second original independent variable calculated value being calculated by the second data provider device according to a second original independent variable and a second model parameter; calculating a dependent variable estimation value according to a first model parameter initial value of a first provider device, a first original independent variable of the first data provider device, and the second original independent variable calculated value; calculating a difference between a dependent variable of the first data provider device and the dependent variable estimation value; calculating a gradient of a loss function with respect to a first model parameter, according to the difference; and updating the first model parameter according to the gradient of the loss function with respect to the first model parameter.
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公开(公告)号：US12026547B2
公开(公告)日：2024-07-02
申请号：US17349788
申请日：2021-06-16
CPC classification number: G06F9/4881 , G06F16/22 , G06F16/258 , G06Q10/10 , G16Y10/75 , H04L67/10
Abstract: A method and a system for arranging business process, a computing device, and a non-transitory computer readable storage medium are provided. The method includes: receiving an application module and a business process rule that are transmitted by a user terminal, wherein the application module is configured to indicate a processing logic in a link in a business process, and wherein the business process rule is configured to indicate a processing rule of the application module; determining a target edge device corresponding to the application module; and transmitting the application module and the business process rule to the target edge device for the target edge device to execute the application module according to the business process rule.
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403.发明授权公开(公告)号：US12020467B2
公开(公告)日：2024-06-25
申请号：US17037144
申请日：2020-09-29
Inventor： Jingbo Zhou , Renjun Hu , Airong Jiang , Jianguo Duan , Hui Xiong
CPC classification number: G06V10/454 , G01C21/3608 , G01C21/3682 , G06F18/2113 , G06N3/045 , G06V10/761 , G06V10/82
Abstract: The present disclosure provides a method for optimizing a tag of a point of interest s(POI). The method includes: obtaining first portrait feature data of each POI in a plurality of POIs and second portrait feature data of each tag in a plurality of marked tags corresponding to the plurality of POIs; mapping the first portrait feature data of each POI and the second portrait feature data of each tag to a metric space to obtain a first feature vector of each POI and a second feature vector of each tag; and optimizing at least one marked tag corresponding to a target POI based on a vector similarity between a first feature vector of the target POI and a second feature vector of at least one tag. The present disclosure provides an apparatus for optimizing a tag of a POI, an electronic device and a computer readable medium.
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404.发明授权公开(公告)号：US12014170B2
公开(公告)日：2024-06-18
申请号：US17397185
申请日：2021-08-09
Inventor： Hao Zhang , Yuanxu Liu , Ke Tao
Abstract: A mini program batch processing method and apparatus, an electronic device, and a readable storage medium are provided. A method includes: establishing a batch package submission creation event; creating, in response to the batch package submission creation event, a batch package submission task to generate a package submission work queue comprising a plurality of mini program package submission tasks; extracting a first quantity of mini program package submission tasks from the package submission work queue; creating a virtual mini program package for each of the first quantity of mini program package submission tasks; and updating the virtual mini program package to a mini program online package and automatically releasing the mini program online package.
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405.发明授权公开(公告)号：US11995405B2
公开(公告)日：2024-05-28
申请号：US17348104
申请日：2021-06-15
Inventor： Xuan Ouyang , Shuohuan Wang , Chao Pang , Yu Sun , Hao Tian , Hua Wu , Haifeng Wang
Abstract: The present disclosure provides a multi-lingual model training method, apparatus, electronic device and readable storage medium and relates to the technical field of deep learning and natural language processing. A technical solution of the present disclosure when training the multi-lingual model is: obtaining training corpuses comprising a plurality of bilingual corpuses and a plurality of monolingual corpuses; training a multi-lingual model with a first training task by using the plurality of bilingual corpuses; training the multi-lingual model with a second training task by using the plurality of monolingual corpuses; and completing the training of the multi-lingual model in a case of determining that loss functions of the first training task and second training task converge. In the present disclosure, the multi-lingual model can be enabled to achieve semantic interaction between different languages and improve the accuracy of the multi-lingual model in learning the semantic representations of the multi-lingual model.
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Patent Agency Ranking
公开(公告)号：US20240166243A1
公开(公告)日：2024-05-23
申请号：US17796074
申请日：2022-01-30
Inventor： Xin ZHANG
IPC: B60W60/00
CPC classification number: B60W60/00253 , B60W2420/403 , B60W2556/10 , B60W2556/40 , B60W2556/45
Abstract: Provided are an automatic driving-based riding method, apparatus and device, and a storage medium. The automatic driving-based riding method includes: selecting a target pick-up point for a target passenger from candidate pick-up points according to vehicle auxiliary information of the candidate pick-up points, where the vehicle auxiliary information of the candidate pick-up points includes coordinate information and lane information of the candidate pick-up points; and controlling an automatic driving vehicle to drive to the target pick-up point according to the vehicle auxiliary information of the target pick-up point.
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407.发明授权公开(公告)号：US11930307B2
公开(公告)日：2024-03-12
申请号：US17204122
申请日：2021-03-17
Inventor： Kangkang Wang
CPC classification number: H04N9/67 , G06T3/4007 , G06T5/50 , G06T2207/10024 , G06T2207/20021 , G06T2207/20221
Abstract: The present application provides an image processing method, an image processing apparatus, an electronic device and a computer-readable storage medium, and relates to the field of image processing technologies. An implementation includes: acquiring an image to be processed; converting the image to be processed into a three-channel YUV image; performing a convolution operation on a Y-channel image, a U-channel image and a V-channel image in the three-channel YUV image to generate an R-channel image, a G-channel image and a B-channel image, respectively, and acquiring a three-channel RGB image; and pre-processing the three-channel RGB image. According to the present application, the image pre-processing speed can be improved.
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408.发明授权公开(公告)号：US11928432B2
公开(公告)日：2024-03-12
申请号：US17319189
申请日：2021-05-13
Inventor： Fei Yu , Jiji Tang , Weichong Yin , Yu Sun , Hao Tian , Hua Wu , Haifeng Wang
CPC classification number: G06F40/284 , G06F40/30 , G06N5/04 , G06N20/00 , G06V10/811 , G06V20/30
Abstract: A multi-modal pre-training model acquisition method, an electronic device and a storage medium, which relate to the fields of deep learning and natural language processing, are disclosed. The method may include: determining, for each image-text pair as training data, to-be-processed fine-grained semantic word in the text; masking the to-be-processed fine-grained semantic words; and training the multi-modal pre-training model using the training data with the fine-grained semantic words masked.
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公开(公告)号：US11921276B2
公开(公告)日：2024-03-05
申请号：US17379428
申请日：2021-07-19
Inventor： Xiang Long , Yan Peng , Shufei Lin , Ying Xin , Bin Zhang , Pengcheng Yuan , Xiaodi Wang , Yuan Feng , Shumin Han
IPC: G02B21/24 , G02B21/36 , G06F18/213 , G06F18/214
CPC classification number: G02B21/244 , G02B21/367 , G06F18/213 , G06F18/214
Abstract: Provided are a method and apparatus for evaluating image relative definition, a device and a medium, relating to technologies such as computer vision, deep learning and intelligent medical. A specific implementation solution is: extracting a multi-scale feature of each image in an image set, where the multi-scale feature is used for representing definition features of objects having different sizes in an image; and scoring relative definition of each image in the image set according to the multi-scale feature by using a relative definition scoring model pre-trained, where the purpose for training the relative definition scoring model is to learn a feature related to image definition in the multi-scale feature.
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公开(公告)号：US11909886B2
公开(公告)日：2024-02-20
申请号：US17145121
申请日：2021-01-08
Inventor： Yang Meng , Haodong Chen , Yuxiao Song , Hui Wang , Xiangmin Li , Jingqi Cao
CPC classification number: H04L9/3239 , H04L9/0618 , H04L9/0643 , H04L9/3247 , H04L63/0428 , H04L9/50
Abstract: Embodiments of the present disclosure provide methods and apparatuses for blockchain-based multi-party computation, a device and a medium, relate to blockchain technology in the field of computer technology. An embodiment of the method can include: encrypting business data, to obtain a ciphertext of the business data; hashing the ciphertext of the business data, to obtain a hash result of the business data; sending the hash result of the business data to a blockchain node, so that the blockchain node writes the hash result of the business data into a blockchain; and sending the ciphertext of the business data to a target trusted computing module in a target server, for instructing the target trusted computing module to perform multi-party computation based on the ciphertext of the business data and the hash result of the business data in the blockchain.
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