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公开(公告)号：US20230049839A1
公开(公告)日：2023-02-16
申请号：US17974409
申请日：2022-10-26
Inventor： Hao CHEN , Runmei ZHAO , Jizhou HUANG
IPC: G06F16/33 , G06F40/205
Abstract: The present disclosure provides a question answering method and apparatus for query information. The method may include: receiving query information input by a user, and analyzing a query target comprised in the query information; recalling candidate answers from a pre-generated knowledge graph based on the query target, where the knowledge graph is constructed based on inherent data in a map database and dynamic data of historical users, and the dynamic data includes at least one of comment data, search data, or spatiotemporal big data; and returning, in response to that there is a target answer whose matching degree with the query target exceeds a preset threshold in the candidate answers, the target answer to the user.
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12.发明公开公开(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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公开(公告)号：US20240071102A1
公开(公告)日：2024-02-29
申请号：US18092518
申请日：2023-01-03
Inventor： Bin WU , Kai ZHONG , Tongbin ZHANG , Jianzhong YANG , Zhen LU , Deguo XIA , Jizhou HUANG
CPC classification number: G06V20/588 , G06V10/26 , G06V10/42 , G06V10/44 , G06V10/751 , G06V10/806
Abstract: Provided are a lane line recognition method, an electronic device and a storage medium, relating to a technical field of artificial intelligence, in particular to technical fields of intelligent transportation, automatic driving and deep learning. The lane line recognition method includes: extracting a basic feature of an original image; recognizing at least one lane line node in the original image by using the basic feature of the original image; extracting a local feature from the basic feature of the original image by using the at least one lane line node; fusing the basic feature and the local feature; and recognizing a lane line in the original image based on a fused result.
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公开(公告)号：US20230072116A1
公开(公告)日：2023-03-09
申请号：US18049782
申请日：2022-10-26
Inventor： Hao CHEN , Runmei ZHAO , Jizhou HUANG
IPC: G06F16/9537 , G06F16/9535 , G06Q30/02
Abstract: A method and an apparatus for recommending a travel mode, an electronic device; and a storage medium are provided. An implementation is: receiving a request from a user for querying a first point of interest; analyzing a travel type of the user based on the request; obtaining an alternative travel mode based on the travel type in combination with user information; calculating a travel cost corresponding to the alternative travel mode; and recommending at least one travel mode for the user according to the travel cost.
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公开(公告)号：US20220237474A1
公开(公告)日：2022-07-28
申请号：US17721659
申请日：2022-04-15
Inventor： Yanyan LI , Jingbo ZHOU , Jizhou HUANG , Dejing DOU
IPC: G06N5/02 , G06F16/901
Abstract: A method and apparatus for semanticization is provided. The method includes: ascertaining a target coordinate of a to-be-semanticized location; ascertaining, through a pre-built regional spatial index tree, a target region to which the target coordinate of the to-be-semanticized location belongs; and ascertaining semantic information of the to-be-semanticized location based on semantic information of the target region.
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Patent Agency Ranking
公开(公告)号：US20240370719A1
公开(公告)日：2024-11-07
申请号：US18512766
申请日：2023-11-17
Inventor： Congxi XIAO , Jizhou HUANG , Jingbo ZHOU
Abstract: This disclosure provides a data generation method, model training method, electronic device, and medium. The data generation method includes: obtaining urban graph data, the urban graph data including a node set, an edge set and a feature set, wherein the node set includes a central node corresponding to a predetermined urban entity, the edge set includes a neighborhood corresponding to the central node, the neighborhood includes other nodes in the node set connected to the central node via an edge, and the feature set includes features of nodes in the node set; partitioning a target region into at least two sub-regions to obtain a region partition set; obtaining a regional feature of each sub-region by aggregating features corresponding to all nodes in the sub-region; and updating a feature of the central node based on the regional features of the sub-regions in the region partition set to obtain target feature data.
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公开(公告)号：US20230213353A1
公开(公告)日：2023-07-06
申请号：US18183003
申请日：2023-03-13
Inventor： Deguo XIA , Jizhou HUANG , Jianzhong YANG , Yanlei GU , Zhen LU , Tingting CAO , Qiuyang XU
CPC classification number: G01C21/3815 , G06T7/10 , G06T5/002
Abstract: A method of updating a road information, an electronic device, and a storage medium, which relate to an artificial intelligence technology field, in particular to fields of computer vision, deep learning, big data, high-definition map, intelligent transportation, automatic driving and autonomous parking, cloud service, Internet of Vehicles and intelligent cabin technologies. The method includes: processing image data corresponding to a target road region to obtain a set of first road lines; obtaining a set of second road lines according to a trajectory map corresponding to the target road region; calibrating the set of first road lines by using the set of second road lines to obtain a set of third road lines; combining the set of third road lines and a set of historical road lines corresponding to the target road region to obtain a combination result; and updating the set of historical road lines according to the combination result.
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公开(公告)号：US20230067177A1
公开(公告)日：2023-03-02
申请号：US17749254
申请日：2022-05-20
Inventor： Shiqiang DING , Jizhou HUANG , Di WU
IPC: G06F40/295 , G06F16/33 , G06N5/02
Abstract: The present disclosure discloses a broadcast style determination method and apparatus, a device and a computer storage medium, and relates to voice and deep learning technologies in the field of artificial intelligence technologies. A specific implementation solution involves: performing named entity recognition on broadcast text to obtain at least one named entity; acquiring domain knowledge corresponding to the at least one named entity; and performing sentiment analysis by using the broadcast text and the domain knowledge, to determine a broadcast style of the broadcast text.
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公开(公告)号：US20240344832A1
公开(公告)日：2024-10-17
申请号：US18747669
申请日：2024-06-19
Inventor： Deguo XIA , Xiyan LIU , Jizhou HUANG
CPC classification number: G01C21/32 , G01C21/3804 , G06F16/29
Abstract: A training method for a map-generation large model is provided, including: obtaining a training sample set, each training sample in the training sample set including a road top-view sample, a first vectorized point set and a first category of a first road element, and a first mask of the road top-view sample; inputting the road top-view sample into an initial map-generation large model, and correspondingly outputting a second vectorized point set and a second category of the second road element, and a second mask of the road top-view sample; determining a model loss according to a matching result between the second and first road element, the first vectorized point set, the first category, the first mask, the second vectorized point set, the second category and the second mask, and adjusting a parameter of the initial map-generation large model according to the model loss to obtain a map-generation large model.
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公开(公告)号：US20240282103A1
公开(公告)日：2024-08-22
申请号：US18654477
申请日：2024-05-03
Inventor： Congxi XIAO , Jizhou HUANG , Jingbo ZHOU
CPC classification number: G06V20/176 , G06V10/26 , G06V10/761 , G06V10/82
Abstract: A data updating method, a model training method and related devices are provided. The method includes obtaining urban graph data in a preset region, the urban graph data including a node set including central nodes, an edge set and a feature set, the edge set including neighborhoods corresponding to the central nodes, the neighborhoods including other nodes possessing connecting edges with the central nodes, the neighborhoods corresponding to a target region, and the feature set including node features of the nodes in the node set; partitioning the target region into at least two sub-regions to obtain a region partition set; aggregating the node features corresponding to all nodes located within the same sub-region to obtain the regional features of each of the sub-regions; updating the node features of the central node based on the regional features of the sub-regions in the region partition set to obtain target feature data.
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