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公开(公告)号:US20230112576A1
公开(公告)日:2023-04-13
申请号:US18053303
申请日:2022-11-07
Inventor: Haocheng LIU , Cai CHEN , Bohao FENG , Shijie XU , Jian TIAN
IPC: G06N3/047
Abstract: Data processing techniques are provided. The techniques include: obtaining a first prediction data set, a model feature list and configuration information, wherein the model feature list indicates a plurality of features required by a data analysis model; generating a second prediction data set based on the model feature list and the first prediction data set, wherein the feature dimension of prediction data in the second prediction data set is smaller than the feature dimension of prediction data in the first prediction data set; performing feature transformation on a feature of the prediction data in the second prediction data set based on the configuration information to generate a third prediction data set; and inputting the third prediction data set into the data analysis model to obtain a prediction result.
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公开(公告)号:US20230121838A1
公开(公告)日:2023-04-20
申请号:US17954767
申请日:2022-09-28
Inventor: Bohao FENG , Yuxin LIU
IPC: G06F40/279 , G06V20/40 , G06V10/86 , G06N3/04
Abstract: There is provided a video question answering method and apparatus, an electronic device and a storage medium, which relates to the field of artificial intelligence, such as natural language processing technologies, deep learning technologies, voice recognition technologies, knowledge graph technologies, computer vision technologies, or the like. The method includes: determining M key frames for a video corresponding to a to-be-answered question, M being a positive integer greater than 1 and less than or equal to a number of video frames in the video; and determining an answer corresponding to the question according to the M key frames.
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公开(公告)号:US20230052906A1
公开(公告)日:2023-02-16
申请号:US17963453
申请日:2022-10-11
Inventor: Yushen CHEN , Hongda YUE , Haiyang XU , Guangyao HAN , Liangjie ZHANG , Wenhao FANG , Bohao FENG , Fei XIAO , Liangxu QUAN
IPC: G06V10/22 , G06V10/82 , G06F40/295
Abstract: An entity recognition method and apparatus, an electronic device, a storage medium, and a computer program product are provided. The method includes: recognizing a to-be-recognized image to determine a preliminary recognition result for entities in the to-be-recognized image; determining, in response to determining that the preliminary recognition result includes a plurality of entities of a same category, image features of the to-be-recognized image and textual features of the plurality of entities; determining whether the plurality of entities is a consecutive complete entity based on the image features and the textual features, to obtain a complete-entity determining result; and obtaining a final recognition result based on the preliminary recognition result and the complete-entity determining result.
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公开(公告)号:US20230038645A1
公开(公告)日:2023-02-09
申请号:US17967761
申请日:2022-10-17
Inventor: Bohao FENG
Abstract: A method for remote damage assessment of a vehicle is provided. The present disclosure relates to the technical field of artificial intelligence, in particular to the technical field of image and text recognition. An implementation solution is: performing data collection on a target vehicle to determine damage information of the target vehicle; obtaining call content of an insurance claiming call for the target vehicle, and extracting accident-related information from the call content, wherein the accident-related information includes named entities in the call content and a relationship between the named entities; and determining a first fraud probability corresponding to the target vehicle at least based on the damage information and the accident-related information.
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公开(公告)号:US20220130160A1
公开(公告)日:2022-04-28
申请号:US17568192
申请日:2022-01-04
Inventor: Bohao FENG , Xiaoshuai ZHANG
IPC: G06V30/146 , G06V30/19 , G06V10/70 , G06V10/82
Abstract: An object recognition method related to the field of artificial intelligence comprises: collecting an object to be subjected to recognition (S101); according to a target text detection model corresponding to the object to be subjected to recognition, carrying out screening and recognition on full text information corresponding to the object to be subjected to recognition, so as to obtain point-of-interest text information therefrom (S102); and carrying out recognition on the point-of-interest text information according to a preset text recognition model (S103). A target text detection model obtains point-of-interest text information by means of carrying out screening and recognition on full text information, such that the recognition of full text information in the prior art is avoided, thus saving recognition time, and improving the recognition efficiency.
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