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公开(公告)号：US20230283655A1
公开(公告)日：2023-09-07
申请号：US18097607
申请日：2023-01-17
Inventor： Mengbo LIU , Zhi FENG
IPC: H04L67/1008 , H04L67/1023
CPC classification number: H04L67/1008 , H04L67/1023
Abstract: A data download technical solution is disclosed. The solution relates to the technical field of artificial intelligence such as cloud computing and big data. The data download method includes receiving a data download request, the data download request including at least one data download task; judging whether the data download request is a new request, request content of which is different from that of a historical data download request; and acquiring a download result corresponding to the at least one data download task based on a judgment result.
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公开(公告)号：US20230282016A1
公开(公告)日：2023-09-07
申请号：US17898678
申请日：2022-08-30
Inventor： Huihui HE , Jiayang WANG , Yubo XIANG
CPC classification number: G06V30/19187 , G06N3/08 , G06T9/002 , G06V30/19147 , G06V30/1916
Abstract: Provided are method for recognizing a receipt, an electronic device and a storage medium, which relate to the fields of deep learning and pattern recognition. The method may include: a target receipt to be recognized is acquired; two-dimensional position information of multiple text blocks on the target receipt respectively is encoded, to obtain multiple encoding results; graph convolution is performed on the multiple encoding results respectively, to obtain multiple convolution results; and each of the multiple convolution results is recognized based on a first conditional random field model, to obtain a first prediction result at text block-level of the target receipt, wherein the first conditional random field model and a second conditional random field model are co-trained, so as to obtain a second prediction result at token-level of the target receipt.
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公开(公告)号：US11741726B2
公开(公告)日：2023-08-29
申请号：US17494682
申请日：2021-10-05
Inventor： Yingying Li , Xiao Tan , Hao Sun
IPC: G06V20/56 , G06T7/194 , G06T7/70 , G06V20/54 , G06V10/22 , G08G1/01 , G06F18/23 , G06F18/2431 , G06F18/2413
CPC classification number: G06V20/588 , G06F18/23 , G06F18/2431 , G06F18/24137 , G06T7/194 , G06T7/70 , G06V10/22 , G06V20/54 , G08G1/0133 , G06T2207/30256
Abstract: A lane line detection method, an electronic device, and a storage medium, related to the field of artificial intelligence, and particularly related to computer vision and deep learning technologies, which can be applied to intelligent traffic scenes, are provided. The method includes: dividing an image into a foreground region and a background region; determining a solid line and a dotted line included in the foreground region; determining, according to the solid line and the dotted line comprised in the foreground region, whether a dotted-and-solid line is included in the foreground region; and determining a lane line detection result according to the solid line, the dotted line, and whether a dotted-and-solid line is comprised in the foreground region. According to the technical solution, the accuracy of lane line detection can be improved.
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公开(公告)号：US20230267357A1
公开(公告)日：2023-08-24
申请号：US17902311
申请日：2022-09-02
Inventor： Xin WANG , Xuanqiang ZHAO , Zhan YU
IPC: G06N10/20
CPC classification number: G06N10/20
Abstract: Provided are a simulation method of a quantum system, a computing device, and a storage medium relating to the field of data processing, and in particular to the field of quantum computing. The method includes: acquiring at least two measurement results; calculating a loss value of a loss function representing an average trace distance; and taking, in the case where the loss value of the loss function satisfies an iteration requirement, a preset parameterized quantum circuit with an adjustable parameter at a first parameter value as a target parameterized quantum circuit.
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公开(公告)号：US20230267060A1
公开(公告)日：2023-08-24
申请号：US17965066
申请日：2022-10-13
Inventor： Yakun MU , Chaoping JI
CPC classification number: G06F11/3452 , G06F9/4881
Abstract: Performance testing method and apparatus, an electronic device, and a storage medium, which relate to the field of computer technology and, for example, the field of cloud computing and server technology. The specific implementation includes: in response to determining that current first performance information of a server does not satisfy a predetermined condition, updating current first concurrency according to the first performance information to obtain second concurrency; performing pressure testing on the server according to the second concurrency to obtain second performance information of the server; and in response to determining that the first performance information satisfies the predetermined condition, performing a task allocation operation of the server according to the first concurrency.
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Patent Agency Ranking
106.发明公开公开(公告)号：US20230259245A1
公开(公告)日：2023-08-17
申请号：US17867588
申请日：2022-07-18
IPC: G06F3/0481 , H04N5/232 , G06F3/04845
CPC classification number: G06F3/0481 , H04N5/23238 , G06F3/04845
Abstract: The prevent disclosure provides a method and apparatus for adjusting a perspective of a direction indicator, an electronic device, and a storage medium, which includes that: a first area and a second area corresponding to a first direction indicator are acquired, where the first direction indicator is configured to indicate a forward direction in a panorama display scene, the first area is a visible area of the first direction indicator in a graphical user interface, and the second area is an invisible area of the first direction indicator outside the graphical user interface; an initial perspective range corresponding to the second area is acquired; a target perspective range to which a first perspective belongs is determined from the initial perspective range, and a second direction indicator corresponding to the target perspective range is displayed; and the first perspective is adjusted to a second perspective based on the second direction indicator.
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公开(公告)号：US11724716B2
公开(公告)日：2023-08-15
申请号：US17185717
申请日：2021-02-25
Inventor： Liming Xia , Kai Yang , Jingchao Feng , Pengjie Zheng , Tianxiang Cui , Mingsong Wang , Yanting Chen , Rongjing Shang , Jiaxin Sun , Haitao Liu , Xiaochuan Du
IPC: B60W60/00 , B60W30/095 , B60W40/072
CPC classification number: B60W60/0011 , B60W30/095 , B60W40/072 , B60W60/005 , B60W60/0016 , B60W2552/30 , B60W2556/50
Abstract: The present disclosure provides a method and apparatus of determining a guide path, and a method and apparatus of controlling driving of a vehicle. The method of determining the guide path may be performed by a monitoring platform and includes: displaying a map for a predetermined range of a vehicle in response to receiving a guide request transmitted by the vehicle, wherein the map includes a plurality of first track points for the vehicle; changing a position of at least one of the plurality of first track points in the map in response to a target operation on the at least one first track point, so as to obtain a plurality of second track points; determining the guide path for the vehicle according to the plurality of second track points; and transmitting path information indicative of the guide path to the vehicle.
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公开(公告)号：US20230252354A1
公开(公告)日：2023-08-10
申请号：US18179627
申请日：2023-03-07
Inventor： Junyuan SHANG , Shuohuan WANG , Siyu DING , Yanbin ZHAO , Chao PANG , Yu SUN , Hao TIAN , Hua WU , Haifeng WANG
IPC: G06N20/00 , G06F40/40 , G06F40/279
CPC classification number: G06N20/00 , G06F40/40 , G06F40/279
Abstract: A method for pre-training a language model includes: constructing a pre-training language data set, in which the pre-training language data set comprises unsupervised language data and supervised language data; generating a hierarchical multi-template and multi-task language data set based on the pre-training language data set; and pre-training the language model based on the hierarchical multi-template and multi-task language data set.
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109.发明公开公开(公告)号：US20230252295A1
公开(公告)日：2023-08-10
申请号：US18300217
申请日：2023-04-13
Inventor： Shuo LI , Lei NIE , Xiaowen XU
IPC: G06N3/08
CPC classification number: G06N3/08 , G06V10/778
Abstract: A method of generating a multimodal set of samples for an intelligent inspection, and a training method, which relate to a field of an artificial intelligence technology, in particular to fields of deep learning, natural language processing, speech technology, computer vision, big data and so on. The method of generating a multimodal set of samples includes: inputting an environmental sample in a collected multimodal set of environmental samples into a single-modal model matched with a modality of the environmental sample, so as to obtain a model processing result corresponding to the environmental sample; determining an initial set of samples from the multimodal set of environmental samples according to the model processing result; and processing the initial set of samples by means of an active learning, so as to determine the multimodal set of samples.
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公开(公告)号：US20230245339A1
公开(公告)日：2023-08-03
申请号：US17884275
申请日：2022-08-09
Inventor： Guanying CHEN , Xiaoqing YE , Xiao TAN , Hao SUN
CPC classification number: G06T7/73 , G06V20/46 , G06T19/20 , G06T2207/20081 , G06T2219/2004
Abstract: Provided are a method for adjusting a three-dimensional pose, an electronic device, and a storage medium, relates to the field of artificial intelligence, and specifically to computer vision and deep learning technologies. A specific implementation solution includes acquiring a video currently recorded; estimating multiple two-dimensional key points of a virtual three-dimensional model and an initial three-dimensional pose based on multiple image frames; performing contact detection on a target part of the virtual three-dimensional model by using the multiple two-dimensional key points, to obtain a detection result; determining multiple target three-dimensional key points by means of the detection result and multiple initial three-dimensional key points corresponding to the initial three-dimensional pose; and adjusting the initial three-dimensional pose to a target three-dimensional pose by using the multiple initial three-dimensional key points and the multiple target three-dimensional key points.
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