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671.发明公开公开(公告)号：US20230280182A1
公开(公告)日：2023-09-07
申请号：US18055381
申请日：2022-11-14
Inventor： Tianxiong DUAN , Baofeng MA , Daochen CHONG , Yuting LIU
CPC classification number: G01C21/3841 , G01C21/32
Abstract: Provided are a high-precision map data collection method and apparatus, an electronic device, and a storage medium, relating to the field of data processing technology and, in particular, to the field of self-driving technology. The solution includes acquiring high-precision map data collected by a data collection device at a target time; and determining the satellite navigation system time corresponding to the target time and establishing an association between the high-precision map data and the satellite navigation system time.
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公开(公告)号：US20230274161A1
公开(公告)日：2023-08-31
申请号：US17940059
申请日：2022-09-08
Inventor： Jinxing YU , Minlong PENG , Mingming SUN , Ping LI
IPC: G06N5/02 , G06F16/903
CPC classification number: G06N5/022 , G06F16/90335
Abstract: There is provided an entity linking method, an electronic device, and a storage medium, which relates to the technical field of artificial intelligence such as machine learning, natural language processing, and intelligent search. A specific implementation solution involves: acquiring a target entity in a knowledge base and most relevant to a to-be-linked entity in a specified statement; and deciding, based on a linking decision strategy, whether to link the to-be-linked entity to the target entity in the knowledge base.
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公开(公告)号：US20230273932A1
公开(公告)日：2023-08-31
申请号：US17947659
申请日：2022-09-19
Inventor： Xu LI , Yunfeng CAI , Mingming SUN , Ping LI
IPC: G06F16/2458 , G06F16/22
CPC classification number: G06F16/2465 , G06F16/2237
Abstract: A method for discovering causality from data includes acquiring to-be-processed data, and obtaining a covariance matrix of the to-be-processed data; determining a first target column in the covariance matrix, taking the number of columns of the first target column as a first place in a rearrangement sequence, and obtaining a first upper triangular matrix according to the first target column; determining a position of the number of columns of the covariance matrix other than the first target column except the first place in the rearrangement sequence according to the first target column and the first upper triangular matrix, and obtaining an upper triangular matrix in each position determination; obtaining an adjacency matrix according to an upper triangular matrix and a rearrangement sequence obtained in final position determination; and generating directed acyclic graph (DAG) by using the adjacency matrix, and taking the DAG as causality discovery result of the to-be-processed data.
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公开(公告)号：US11741713B2
公开(公告)日：2023-08-29
申请号：US18088082
申请日：2022-12-23
Inventor： Caihong Ma , Guanhao Wang
IPC: G06V20/40 , G06V10/44 , G06F18/25 , G06F18/24 , G06F18/213
CPC classification number: G06V20/41 , G06F18/213 , G06F18/24 , G06F18/253 , G06V10/44
Abstract: A method of detecting an action, an electronic device, and a storage medium. A method can include: performing a temporal action proposal on at least one target feature data obtained by a feature extraction on a plurality of target frame data of a target resource, so as to obtain at least one first candidate action proposal information; classifying target feature data corresponding to at least one first candidate action proposal interval included in the first candidate action proposal information, so as to obtain at least one classification confidence level corresponding to the at least one first candidate action proposal interval; and determining an action detection result for at least one action segment contained in the target resource according to the at least one classification confidence level corresponding to the at least one first candidate action proposal interval, wherein the action detection result includes an action category and an action period.
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675.发明公开公开(公告)号：US20230267286A1
公开(公告)日：2023-08-24
申请号：US17879965
申请日：2022-08-03
Inventor： Liwen Zhang , Meng Sun , Zhongjun He , Zhi Li
IPC: G06F40/58 , G06F40/211
CPC classification number: G06F40/58 , G06F40/211
Abstract: Provided are a translation model training method, a translation method, a device, and a storage medium, and relates to a field of computer technology, and in particular, to artificial intelligence fields such as natural language processing, machine translation and the like. The translation model training method includes: processing a sample document, to obtain an RST discourse structure tree in a dependency form of the sample document, a side in the RST discourse structure tree in the dependency form indicating an RST relationship in a discourse of the sample document; determining an attention mechanism of a translation model to be trained, based on the RST relationship in the RST discourse structure tree in the dependency form; and inputting the RST discourse structure tree in the dependency form and the sample document into the translation model to be trained for training, to obtain a trained translation model.
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Patent Agency Ranking
公开(公告)号：US20230266773A1
公开(公告)日：2023-08-24
申请号：US17884136
申请日：2022-08-09
Inventor： Haodong DING , Liangjun ZHANG
CPC classification number: G05D1/0891 , G05D1/0088 , G05D2201/021
Abstract: Provided are a vehicle attitude estimation method, an electronic device and a storage medium, relates to a technical field of data processing, and in particular to fields of automatic driving, intelligent transportation, Internet of Things, big data and the like. A specific implementation solution includes: obtaining first target data, based on point cloud data of a vehicle, the first target data being capable of constituting a target surface of the vehicle; performing attitude estimation on a target body for surrounding the vehicle, based on the first target data, to obtain an estimation result; and estimating an attitude of the vehicle, based on the estimation result. According to the implementation solution, precise or accurate estimation of the attitude of the vehicle may be achieved.
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677.发明公开公开(公告)号：US20230260144A1
公开(公告)日：2023-08-17
申请号：US17986244
申请日：2022-11-14
CPC classification number: G06T7/55 , G06T3/4007 , G06T2207/10028
Abstract: Provided are a method and apparatus for determining image depth information, an electronic device, and a medium. The method includes: acquiring first depth information of pixels in a target image output by a first prediction layer; generating the point cloud model of the target image according to the first depth information, and determining initial depth information of the pixels in the target image in a second prediction layer according to the point cloud model; and performing propagation optimization according to the initial depth information, and determining second depth information of the pixels in the target image output by the second prediction layer, where the first prediction layer is configured before the second prediction layer.
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公开(公告)号：US20230251769A1
公开(公告)日：2023-08-10
申请号：US18300224
申请日：2023-04-13
Inventor： Yongzheng XIN , Shuangshuang CUI , Wensi SU , Huibin ZHAO
IPC: G06F3/0484 , G06F3/0482 , G06F40/166 , G06F3/0488
CPC classification number: G06F3/0484 , G06F3/0482 , G06F40/166 , G06F3/0488
Abstract: Provided are a method of generating a note, an electronic device, and a storage medium, which relate to a field of artificial intelligence, and in particular to fields of information processing and e-book technology. The method includes: displaying, in a process of displaying an e-book reading page, at least one note combination option for a first note generation instruction, in response to the first note generation instruction being detected; determining a second note generation instruction associated with a target note combination option, in response to an operation of selecting the target note combination option from the at least one note combination option; and combining a current character content associated with the first note generation instruction with a target character content associated with the second note generation instruction, so as to generate a combined note content.
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公开(公告)号：US20230239358A1
公开(公告)日：2023-07-27
申请号：US17896216
申请日：2022-08-26
Inventor： Fenghui Zhang , Yun Gu , Yishuang Geng , Zhuoran Xu
IPC: H04L67/14
CPC classification number: H04L67/14
Abstract: A method for forwarding data, a load balancing device, a computer readable storage medium, and a data transmission system. An implementation of the method includes: obtaining a data packet sent by a client, and extracting an actual session parameter from the data packet; in response to the actual session parameter being an unrecorded session parameter, reading information from a preset field address constituting a packet header of the data packet; wherein a preset field corresponding to the preset field address is configured to record information used to determine a target server parameter; in response to determining that the information read from the preset field address is not empty, determining, based on target information read from the preset field address, the target server parameter as a client communication object; and forwarding the data packet to a target server corresponding to the target server parameter.
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680.发明公开公开(公告)号：US20230232116A1
公开(公告)日：2023-07-20
申请号：US18156187
申请日：2023-01-18
Inventor： Qi Zhang , Dongliang He , Xin Li
IPC: H04N23/741 , G06T3/40 , G06T5/00 , G06T5/50
CPC classification number: H04N23/741 , G06T3/40 , G06T5/007 , G06T5/50 , G06T2207/20081 , G06T2207/20208 , G06T2207/20221
Abstract: Provided are a video conversion method, an electronic device and a non-transitory computer readable storage medium. The implementation scheme is as follows: a to-be-converted SDR video is acquired; one frame is extracted from the to-be-converted SDR video to serve as a current SDR image, the current SDR image is input into a parameter predictor and a generator, and an adjustment parameter corresponding to the current SDR image is output from the parameter predictor; the adjustment parameter corresponding to the current SDR image is input into the generator, and an HDR image corresponding to the current SDR image is output from the generator; and the operation described above is repeatedly performed until frames are converted into HDR images each of which corresponds to a respective frame of the frames; and a corresponding HDR video is generated based on the HDR images corresponding to the frames.
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