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41.发明公开公开(公告)号：US20240338962A1
公开(公告)日：2024-10-10
申请号：US18747599
申请日：2024-06-19
Inventor： Haiwei WANG , Zhongwen ZHANG , Gang LI
IPC: G06V30/414 , G06V30/418
CPC classification number: G06V30/414 , G06V30/418
Abstract: The present disclosure provides an image based human-computer interaction method, which includes: acquiring a to-be-analyzed image, and determining image layout information and image content information of the to-be-analyzed image, where the to-be-analyzed image includes a variety of modal data, the image layout information represents distribution of image elements with preset granularity in the to-be-analyzed image, and the image content information represents a content expressed by the modal data in the to-be-analyzed image; and determining, in response to acquiring question information, response information corresponding to the question information according to the image layout information and the image content information, where the question information represents a question proposed by a user for the to-be-analyzed image, and the response information represents a reply answer corresponding to the question information. By extracting layout information and content information from an image, the accuracy of answering a question and user experience of human-computer interaction are improved.
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公开(公告)号：US12093297B2
公开(公告)日：2024-09-17
申请号：US17577561
申请日：2022-01-18
Inventor： Wenhao Wu , Wei Li , Xinyan Xiao , Jiachen Liu
CPC classification number: G06F16/345 , G06F40/51 , G06F40/56
Abstract: The present disclosure provides a summary generation model training method and apparatus, a device and a storage medium, and relates to the field of computer technologies, and in particular, to the field of artificial intelligence such as natural language processing and deep learning. The summary generation model training method includes: acquiring a document representation corresponding to a document sample; constructing, based on the document representation, a summary representation corresponding to the document representation, the summary representation including a positive summary representation and a negative summary representation; and constructing a total contrastive loss function based on the document representation, the positive summary representation and the negative summary representation, and training a summary generation model based on the total contrastive loss function. The present disclosure may improve accuracy of the summary generation model.
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公开(公告)号：US20240303880A1
公开(公告)日：2024-09-12
申请号：US18020903
申请日：2022-07-25
Inventor： Zhanguo CHANG , Yi LV , Tiansheng DENG , Ting YUN
CPC classification number: G06T11/203 , G06T3/02 , G06T3/60 , G06T7/10 , G06T11/60
Abstract: A method of generating an image sample, which relates to a field of an artificial intelligence technology, in particular to fields of a deep learning technology and a computer vision technology. The method includes: generating a handwritten text image according to at least one handwritten sample image; and generating a target sample image with an annotation box according to the handwritten text image and a background image, where the annotation box is used to represent a region in which the handwritten text image is located in the background image. The present disclosure further provides a method of recognizing a text, an electronic device and a storage medium.
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公开(公告)号：US20240303774A1
公开(公告)日：2024-09-12
申请号：US18020918
申请日：2022-06-10
Inventor： Changyong SHU , Jiaming LIU , Zhibin HONG , Junyu HAN
CPC classification number: G06T5/50 , G06T5/60 , G06T7/40 , G06T7/55 , G06T7/90 , G06V40/172 , G06T2207/10024 , G06T2207/20081 , G06T2207/20084 , G06T2207/20221 , G06T2207/30201
Abstract: A method of processing an image, an electronic device and a storage medium. The method includes: generating a to-be-processed image according to a first target image and a second target image, where an identity information of an object in the to-be-processed image is matched with an identity information of an object in the first target image; generating a set of disentangled images according to the second target image and the to-be-processed image, where the set of disentangled images includes a head-disentangled image and a disentangled repair image; and generating a fusion image according to the set of disentangled images, where an identity information and a texture information of an object in the fusion image are matched with the identity information and the texture information of the object in the to-be-processed image, respectively, and a to-be-repaired information related to the object in the fusion image is repaired.
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45.发明公开公开(公告)号：US20240303430A1
公开(公告)日：2024-09-12
申请号：US18667504
申请日：2024-05-17
Inventor： Meng TIAN , Lin YANG , Xinwei FENG , Zhifan FENG , Xiaopeng CUI , Qiaoqiao SHE , Hua WU
IPC: G06F40/20
CPC classification number: G06F40/20
Abstract: A technical solution for processing a model generation result, which relates to the field of artificial intelligence technologies is disclosed. An implementation includes: disassembling a text generation result of a generative large model to obtain a plurality of result logic units; wherein each result logic unit includes a segment in the text generation result; each segment is capable of independently identifying one premise or conclusion in a logical inference relationship of the text generation result; and the text generation result is a response result generated by the generative large model based on text input information; generating a logical inference graph capable of characterizing a logical inference relationship among the plurality of result logic units based on the plurality of result logic units; and determining whether logical inference of generation of the text generation result by the generative large model is correct or not based on the logical inference graph.
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Patent Agency Ranking
公开(公告)号：US12086171B2
公开(公告)日：2024-09-10
申请号：US17812120
申请日：2022-07-12
Inventor： Yang Zhang , Shuangquan Yang , Lei Han , Keke Zhou , Yi Xie , Wei Zhou , Junyi Chen , Dongjian Shi , Guihua Bai , Xuan Li
IPC: G06F7/00 , G06F16/33 , G06F40/289
CPC classification number: G06F16/3344 , G06F16/3347 , G06F40/289
Abstract: A word mining method and apparatus, an electronic device and a readable storage medium are disclosed. The method includes: acquiring search data; taking first identification information, a search sentence and second identification information in the search data as nodes, and taking a relationship between the first identification information and the search sentence, a relationship between the first identification information and the second identification information and a relationship between the search sentence and the second identification information as sides to construct a behavior graph; obtaining a label vector of each search sentence in the behavior graph according to a search sentence with a preset label in the behavior graph; determining a target search sentence in the behavior graph according to the label vector; and extracting a target word from the target search sentence, and taking the target word as a word mining result of the search data.
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公开(公告)号：US20240281602A1
公开(公告)日：2024-08-22
申请号：US18651183
申请日：2024-04-30
Inventor： Yaqing WANG
IPC: G06F40/20
CPC classification number: G06F40/20
Abstract: A method of processing a text, a training method, a method of generating a knowledge graph, an electronic device, and a non-transitory computer-readable storage medium are provided, which relates to a field of artificial intelligence, particularly to fields such as deep learning, natural language processing, computer vision, and speech processing. The method of processing a text includes: encoding a text to be processed to obtain a feature information; identifying a plurality of entity information from the text, based on the feature information; generating a word relation tensor based on the feature information; and determining a relation between the plurality of entity information by using the word relation tensor, so as to generate a plurality of relational triplets related to the text.
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公开(公告)号：US20240273297A1
公开(公告)日：2024-08-15
申请号：US18642593
申请日：2024-04-22
Inventor： Yu LI , Jiawei ZHENG , Xinjiang LU , Hongwei XIE , Xuejiao LIN , Jingbo ZHOU
IPC: G06F40/295
CPC classification number: G06F40/295
Abstract: An entity recognition method, a model training method, an electronic device, and a medium, which relate to fields of artificial intelligence, information acquiring technologies. The entity recognition method includes: extracting specified entities from a text in a source file of a webpage to be recognized, and acquiring a text encoding result for each specified entity; determining a text block formed by each specified entity in the webpage, and encoding a relative layout information between each two text blocks, to obtain a position encoding result; constructing a triple by the position encoding result for each two text blocks and the text encoding results for respective specified entities of the two text blocks; and performing a graph convolution on each triple to obtain a relation recognition result for the webpage to be recognized, where the relation recognition result indicates whether an association exists between each two text blocks in the webpage.
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公开(公告)号：US20240265687A1
公开(公告)日：2024-08-08
申请号：US18020396
申请日：2022-04-22
Inventor： Bi LI , Nan PENG , Teng XI , Gang ZHANG
CPC classification number: G06V10/806 , G06V10/7715
Abstract: A method of fusing an image feature, an electronic device, and a storage medium are provided, which relate to the field of artificial intelligence, in particular to fields of computer vision and depth learning, and may be applied to scenarios such as image processing and image recognition. The method includes: inputting an image into a first image processing model among N serially connected image processing models, to obtain an output feature of the first image processing model, an i-th image processing model includes a first shared layer to an i-th shared layer, i=1, . . . , N, and N is a natural number greater than or equal to 2; inputting an output feature of a j-th image processing model into a (j+1)-th image processing model, to obtain an output feature of the (j+1)-th image processing model, j=1, . . . , N−1; and fusing the output features of the N image processing models.
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公开(公告)号：US20240246549A1
公开(公告)日：2024-07-25
申请号：US18003017
申请日：2022-11-28
Inventor： Shu JIANG , Hao LIU , Szu-Hao WU , Fuyang ZHAO , Xiaoyi ZHU , Haofeng KOU , Helen K. PAN
CPC classification number: B60W50/045 , B60W60/00 , B60W2050/0022 , B60W2520/10 , B60W2520/105 , B60W2556/10
Abstract: In one embodiment, a microcontroller unit (MCU) receives an expected state of an autonomous driving vehicle (ADV) from a controller of the ADV, where the controller controls motions of the ADV using a control algorithm. The MCU receives sensor data from one or more sensors of the ADV. The MCU determine an actual state of the ADV based on the sensor data. The MCU determines a performance metric of the control algorithm based on the expected state and the actual state. In response to determining the performance metric has satisfied a predetermined condition, the MCU determines a plurality of weight values for the control algorithm. The MCU sends the plurality of weight values to the control system to tune one or more weight parameters of the control algorithm using the plurality of weight values, where the controller controls the ADV using the tuned control algorithm.
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