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公开(公告)号：US20230177821A1
公开(公告)日：2023-06-08
申请号：US18063564
申请日：2022-12-08
Inventor： Qiming PENG , Bin LUO , Yuhui CAO , Shikun FENG , Yongfeng CHEN
CPC classification number: G06V10/82 , G06V30/19147 , G06V30/1444
Abstract: A neural network training method and a document image understanding method is provided. The neural network training method includes: acquiring text comprehensive features of a plurality of first texts in an original image; replacing at least one original region in the original image to obtain a sample image including a plurality of first regions and a ground truth label for indicating whether each first region is a replaced region; acquiring image comprehensive features of the plurality of first regions; inputting the text comprehensive features of the plurality of first texts and the image comprehensive features of the plurality of first regions into a neural network model together to obtain text representation features of the plurality of first texts; determining a predicted label based on the text representation features of the plurality of first texts; and training the neural network model based on the ground truth label and the predicted label.
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公开(公告)号：US20230177359A1
公开(公告)日：2023-06-08
申请号：US18063348
申请日：2022-12-08
Inventor： Sijin WU , Han LIU , Teng HU , Shikun FENG , Yongfeng CHEN
IPC: G06N5/022 , G06F40/174 , G06F40/205
CPC classification number: G06N5/022 , G06F40/174 , G06F40/205 , G06F40/30
Abstract: The present disclosure provides a method and apparatus for training a document information extraction model and method and apparatus for extracting document information, and relates to the field of artificial intelligence, and more particularly to the field of natural language processing. A specific implementation solution is: acquiring training data labeled with an answer corresponding to a preset question and a document information extraction model, the training data includes layout document training data and streaming document training data; extracting at least one feature from the training data; fusing at least one feature to obtain a fused feature; inputting the preset question, the fused feature and the training data into the document information extraction model to obtain a predicted result; and adjusting network parameters of the document information extraction model based on the predicted result and the answer.
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公开(公告)号：US20230135536A1
公开(公告)日：2023-05-04
申请号：US18089395
申请日：2022-12-27
Inventor： Chenhui LI , Teng HU , Shikun FENG , Yongfeng CHEN
Abstract: A method and an apparatus for processing a table are provided. The method includes: obtaining text information of cells in the table; obtaining structure information of the cells in the table; and inputting a query word, the text information, and the structure information of the table into a table information extraction model to obtain an answer output from the table information extraction model, wherein the output answer corresponds to the query word in the table.
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公开(公告)号：US20230097986A1
公开(公告)日：2023-03-30
申请号：US18058640
申请日：2022-11-23
Inventor： Han LIU , Teng HU , Yongfeng CHEN
IPC: G06F40/279 , G06F40/30
Abstract: A data processing method is provided. The method includes: determining fusion information based on a text to be processed and a plurality of reference text fragments; executing the following matching operation for each of the plurality of reference text fragments: determining a first coefficient of each feature vector of the fusion information respectively; determining a second coefficient of each feature vector of the fusion information respectively; determining a result feature vector of the reference text fragment using each feature vector included in the fusion information and a weight of the feature vector; and determining a matching degree of the reference text fragment and the text to be processed based on the result feature vector.
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Patent Agency Ranking
5.发明申请公开(公告)号：US20230005283A1
公开(公告)日：2023-01-05
申请号：US17577531
申请日：2022-01-18
Inventor： Han LIU , Teng HU , Yongfeng CHEN
IPC: G06V30/18 , G06V30/19 , G06V30/262 , G06F40/20
Abstract: The present disclosure provides an information extraction method and apparatus, an electronic device and a readable storage medium, and relates to the field of natural language processing technologies. The information extraction method includes: acquiring a to-be-extracted text; acquiring a sample set, the sample set including a plurality of sample texts and labels of sample characters in the plurality of sample texts; determining a prediction label of each character in the to-be-extracted text according to a semantic feature vector of each character in the to-be-extracted text and a semantic feature vector of each sample character in the sample set; and extracting, according to the prediction label of each character, a character meeting a preset requirement from the to-be-extracted text as an extraction result of the to-be-extracted text. The present disclosure can simplify steps of information extraction, reduce costs of information extraction and improve flexibility and accuracy of information extraction.
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6.发明申请公开(公告)号：US20220382991A1
公开(公告)日：2022-12-01
申请号：US17883908
申请日：2022-08-09
Inventor： Qiming PENG , Bin LUO , Yuhui CAO , Shikun FENG , Yongfeng CHEN
IPC: G06F40/30 , G06V30/414 , G06V30/14
Abstract: The present disclosure provides a training method and apparatus for a document processing model, a device, a storage medium and a program, which relate to the field of artificial intelligence, and in particular, to technologies such as deep learning, natural language processing and text recognition. The specific implementation is: acquiring a first sample document; determining element features of a plurality of document elements in the first sample document and positions corresponding to M position types of each document element according to the first sample document; where the document element corresponds to a character or a document area in the first sample document; and performing training on a basic model according to the element features of the plurality of document elements and the positions corresponding to the M position types of each document element to obtain the document processing model.
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公开(公告)号：US20220108556A1
公开(公告)日：2022-04-07
申请号：US17552149
申请日：2021-12-15
Inventor： Yiyu PENG , Teng HU , Hua LU , Yongfeng CHEN
IPC: G06V30/418 , G06V30/412 , G06V30/10 , G06F40/103 , G06F16/93
Abstract: A method of comparing documents, an electronic device, and a readable storage medium are provided, which relate to the field of data processing technology, and specifically to the field of big data technology. In the present disclosure, an area division is performed on each document of two documents to be compared, according to a document layout of each document, so as to obtain at least two sets of comparison units. Each set of comparison units comprises comparison units for the two documents respectively and the comparison units for the two documents correspond to each other. Thus, a content comparison may be performed on between comparison units of each of the at least two sets, so as to obtain a content comparison result for each set of comparison units as a comparison result for the two documents.
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公开(公告)号：US20210406619A1
公开(公告)日：2021-12-30
申请号：US17169112
申请日：2021-02-05
Inventor： Pengyuan LV , Xiaoqiang ZHANG , Shanshan LIU , Chengquan ZHANG , Qiming PENG , Sijin WU , Hua LU , Yongfeng CHEN
IPC: G06K9/72 , G06T7/70 , G06F40/30 , G06K9/46 , G06K9/00 , G06K9/32 , G06K9/20 , G06K9/62 , G06N20/00 , G06N5/04
Abstract: The present disclosure provides a method for visual question answering, which relates to fields of computer vision and natural language processing. The method includes: acquiring an input image and an input question; detecting visual information and position information of each of at least one text region in the input image; determining semantic information and attribute information of each of the at least one text region based on the visual information and the position information; determining a global feature of the input image based on the visual information, the position information, the semantic information, and the attribute information; determining a question feature based on the input question; and generating a predicted answer for the input image and the input question based on the global feature and the question feature. The present disclosure further provides a device for visual question answering, a computer device and a medium.
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公开(公告)号：US20220231504A1
公开(公告)日：2022-07-21
申请号：US17684131
申请日：2022-03-01
Inventor： Hongsheng ZENG , Bo ZHOU , Kejiao LI , Fan WANG , Yongfeng CHEN , Jingzhou HE
Abstract: A method for training a power system scheduling model includes: generating a plurality of first scheduling sub-models based on a first initial scheduling model; acquiring a first matching degree of historical running state information and each of candidate actions, output by each of the plurality of first scheduling sub-models, by inputting the historical running state information into each of the plurality of first scheduling sub-models; generating a second initial scheduling model by correcting the first initial scheduling model based on first matching degrees corresponding to each of the plurality of first scheduling sub-models; and returning to the generating the plurality of first scheduling sub-models based on the second initial scheduling model, until the matching degree output by the second initial scheduling module meets the convergence condition, determining the second initial scheduling model as the power system scheduling model.
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