-
公开(公告)号：US12300012B2
公开(公告)日：2025-05-13
申请号：US17984034
申请日：2022-11-09
Inventor： Shangwen Lyu , Hongyu Li , Jing Liu , Hua Wu , Haifeng Wang
IPC: G06V30/19 , G06F40/205 , G06V30/194 , G06V30/412
Abstract: A method for training a document reading comprehension model includes: acquiring a question sample and a rich-text document sample, in which the rich-text document sample includes a real answer of the question sample; acquiring text information and layout information of the rich-text document sample by performing OCR processing on image information of the rich-text document sample; acquiring a predicted answer of the question sample by inputting the text information, the layout information and the image information of the rich-text document sample into a preset reading comprehension model; and training the reading comprehension model based on the real answer and the predicted answer. The method may enhance comprehension ability of the reading comprehension model to the long rich-text document, and save labor cost.
-
公开(公告)号：US20250139327A1
公开(公告)日：2025-05-01
申请号：US18895722
申请日：2024-09-25
Inventor： Liang Shen , Jinle Zeng , Hongxiang Hao , Weibao Gong , Dianhai Yu , Haifeng Wang
IPC: G06F30/20
Abstract: A method for processing a model operator includes: determining an operator set for model networking, wherein the operator set comprises a plurality of operators; determining a storage amount occupied by an output tensor of each operator in the operator set and a computation time period consumed in a forward computation of each operator in the operator set; and determining a first operator participating in recomputation in a model from the operator set, based on the storage amounts and the computation time periods of the plurality of operators.
-
公开(公告)号：US12282746B2
公开(公告)日：2025-04-22
申请号：US17820765
申请日：2022-08-18
Inventor： Haifeng Wang , Zhanyi Liu , Zhongjun He , Hua Wu , Zhi Li , Xing Wan , Jingxuan Zhao , Ruiqing Zhang , Chuanqiang Zhang , Fengtao Huang , Hanbing Song , Wei Di , Shuangshuang Cui , Yongzheng Xin
IPC: G06F40/58
Abstract: A display method, an electronic device, and a storage medium, which relate to a field of natural language processing and a field of display. The display method includes: acquiring a content to be displayed; extracting a target term from the content using a term extraction rule; acquiring an annotation information for at least one target term, responsive to an extraction of the at least one target term; and displaying the annotation information for the at least one target term and the content.
-
公开(公告)号：US20250029010A1
公开(公告)日：2025-01-23
申请号：US18895264
申请日：2024-09-24
Inventor： Dianhai Yu , Gexiao Tian , Weibao Gong , Haifeng Wang , Yongsheng Xu , Jiabin Yang
IPC: G06N20/00
Abstract: A cluster-based training method includes: in response to a hardware fault in the training node, selecting a target standby node from the plurality of standby nodes, and obtaining a target training snapshot of the model training task in the training node, in which the target training snapshot includes training state data of the model training task; and initializing the target standby node based on a container image of a model training program in the training node and the training state data to replace the training node with the target standby node to continue executing the model training task.
-
公开(公告)号：US12183324B2
公开(公告)日：2024-12-31
申请号：US17738651
申请日：2022-05-06
Inventor： Xiaoyin Fu , Zhijie Chen , Mingxin Liang , Mingshun Yang , Lei Jia , Haifeng Wang
IPC: G10L15/02 , G06F16/683 , G10L15/187 , G10L15/26
Abstract: The present disclosure provides speech recognition and codec methods and apparatuses, an electronic device and a storage medium, and relates to the field of artificial intelligence such as intelligent speech, deep learning and natural language processing. The speech recognition method may include: acquiring an audio feature of to-be-recognized speech; encoding the audio feature to obtain an encoding feature; truncating the encoding feature to obtain continuous N feature fragments, N being a positive integer greater than one; and acquiring, for any one of the feature segments, corresponding historical feature abstraction information, encoding the feature segment in combination with the historical feature abstraction information, and decoding an encoding result to obtain a recognition result corresponding to the feature segment, wherein the historical feature abstraction information is information obtained by feature abstraction of recognized historical feature fragments.
-
Patent Agency Ranking
公开(公告)号：US11983086B2
公开(公告)日：2024-05-14
申请号：US17989644
申请日：2022-11-17
Inventor： Haifeng Wang , Xiaoguang Hu , Dianhai Yu , Xiang Lan , Yanjun Ma
CPC classification number: G06F11/3409 , G06N3/063
Abstract: The disclosure provides a method for processing data, and an electronic device. The method includes: obtaining first attribute information of input data and second attribute information of a computing device corresponding to the input data; selecting a target operator implementation mode from a plurality of candidate operator implementation modes based on the first attribute information and the second attribute information; determining a plurality of sub-operators included in an operator required for the input data from an operator library based on the target operator implementation mode, to generate the operator; and obtaining an operation result by performing an operation on the input data by the computing device based on the operator.
-
公开(公告)号：US20240062654A1
公开(公告)日：2024-02-22
申请号：US17753817
申请日：2021-11-17
Inventor： Jizhou Huang , Deguo Xia , Haifeng Wang
IPC: G08G1/0968 , G08G1/01 , G08G1/0967 , G08G1/052
CPC classification number: G08G1/0968 , G08G1/0145 , G08G1/0112 , G08G1/096725 , G08G1/052
Abstract: The present disclosure discloses a vehicle control method and apparatus, a device and a computer storage medium, and relates to the technical fields of autonomous driving and intelligent transportation. A specific implementation solution involves: determining vehicles in a preset geo-fencing region; determining a vehicle weight of each said vehicles according to a vehicle type and a waiting duration of each said vehicles; estimating, according to the vehicle weights of the vehicles in each of lanes in the geo-fencing region and positions of the vehicles in each said lanes, a duration to be waited in each said lanes; and generating a control instruction for each said vehicles according to the respective durations to be waited in each said lanes and the respective positions of the vehicles in each said lanes, the control instruction including a state instruction and/or a target speed instruction. According to the present disclosure, global scheduling decisions can be performed on vehicles in a geo-fencing region, so as to alleviate traffic congestion.
-
公开(公告)号：US20230213388A1
公开(公告)日：2023-07-06
申请号：US17998881
申请日：2020-10-14
Inventor： Haocheng Feng , Haixiao Yue , Keyao Wang , Gang Zhang , Yanwen Fan , Xiyu Yu , Junyu Han , Jingtuo Liu , Errui Ding , Haifeng Wang
IPC: G01J5/00
CPC classification number: G01J5/0025 , G01J2005/0077
Abstract: A method and an apparatus for measuring temperature, and a computer-readable storage medium includes detecting a target position of an object in an input image; determining key points of the target position and weight information of each key point based on a detection result of the target position, in which the weight information is configured to indicate a probability of each key point being covered; acquiring temperature information of each key point; and determining a temperature of the target position at least based on the temperature information and the weight information of each key point.
-
9.发明申请公开(公告)号：US20220327809A1
公开(公告)日：2022-10-13
申请号：US17809133
申请日：2022-06-27
Inventor： Wei Li , Can Gao , Guocheng Niu , Xinyan Xiao , Hao Liu , Jiachen Liu , Hua Wu , Haifeng Wang
IPC: G06V10/778 , G06V10/774 , G06V10/26 , G06F40/284
Abstract: A method for training a model based on multi-modal data joint learning, includes: obtaining multi-modal data; in which the multi-modal data include at least one type of single-modal data and at least one type of Pair multi-modal data; inputting the single-modal data and the Pair multi-modal data into a decoupling attention Transformer network model to generate respectively Token semantic representation features and cross-modal semantic representation features; and training the decoupling attention Transformer network model based on the Token semantic representation features and the cross-modal semantic representation features.
-
公开(公告)号：US20220222111A1
公开(公告)日：2022-07-14
申请号：US17707895
申请日：2022-03-29
Inventor： Haifeng Wang , Xiaoguang HU , Dianhai YU , Yanjun MA , Tian WU
Abstract: A scheduling method for a deep learning framework, a scheduling apparatus, an electronic device, a storage medium, and a program product is provided, and can be used in the field of artificial intelligence, especially in the fields of machine learning, deep learning, etc. The method includes: receiving a processing request for processing a plurality of tasks by using a dedicated processing unit, the processing request including scheduling requirements for the plurality of tasks, and each of the plurality of tasks being associated with execution of multi-batch data processing; and scheduling, based on the scheduling requirements for the plurality of tasks in batches of data, the dedicated processing unit to process the plurality of tasks.
-
-
-
-
-
-
-
-
-
Search Results
42
records
(took 0.044 seconds)
