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公开(公告)号：US20240419991A1
公开(公告)日：2024-12-19
申请号：US18747725
申请日：2024-06-19
Inventor： Zhenfang CHU , Zhengyu QIAN , En SHI , Mingren HU , Zhengxiong YUAN , Jinqi LI , Yue HUANG , Yang LUO , Guobin WANG , Yang QIAN , Kuan WANG
IPC: G06N5/04
Abstract: A method is provided that includes: creating a plurality of first model instances of a first service model to be deployed; allocating an inference service for each of a plurality of first model instances from the plurality of inference services; calling, for each first model instance, a loading interface of the inference service allocated for the first model instance to mount a weight file; determining, in response to a user request for a target service model, a target model instance from a plurality of model instances of the target service model to respond to the user request; and calling a target inference service allocated for the target model instance to use computing resources configured for the target inference service to run, in the target model instance, a base model mounted with a target weight file, and obtain a request result of the user request.
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公开(公告)号：US20240419484A1
公开(公告)日：2024-12-19
申请号：US18817035
申请日：2024-08-27
IPC: G06F9/48
Abstract: A method for processing information is provided. The method includes obtaining input information to be processed. The method further includes determining execution information associated with processing of the input information. The execution information includes at least one of memory information to be retrieved or tool information to be invoked. The method further includes obtaining, by using the execution information, at least one piece of processing result information corresponding to the processing of the input information. The method further includes the at least one piece of processing result information to generate output information for feedback.
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公开(公告)号：US20240412438A1
公开(公告)日：2024-12-12
申请号：US18747627
申请日：2024-06-19
Inventor： Xirui FAN , Yafei ZHAO , Zongcai DU , Yi CHEN , Zhiqiang WANG
Abstract: The present disclosure provides a mouth shape-based method for generating a face image, a method for training a model, and a device, which relates to the field of artificial intelligence, in particular to the field of cloud computing and digital human. The specific implementation solution is as follows: acquiring audio data to be recognized and a preset face image; determining an audio feature of the audio data to be recognized; where the audio feature includes a speech speed feature and a semantic feature; and performing, according to the speech speed feature and the semantic feature, processing on the preset face image, to generate a face image having a mouth shape.
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44.发明申请公开(公告)号：US20240411552A1
公开(公告)日：2024-12-12
申请号：US18748345
申请日：2024-06-20
Inventor： Jing XIA , Jun LIU , Binbin XU , Kuan SHI , Shupeng LI , Zhengyu QIAN , En SHI
Abstract: A computer-implemented method for recommending a large model interface configuration includes: obtaining a search space of a model interface configuration and a test data set, wherein the search space comprises at least one candidate model interface and a value range of a hyperparameter; and obtaining a plurality of model interface configuration sets based on the search space, wherein each model interface configuration set comprises a candidate model interface and a value of the hyperparameter; and obtaining a test result corresponding to each model interface configuration set, by using the test data set to test a large model called based on each model interface configuration set; and determining a target interface configuration based on the test results corresponding to the plurality of model interface configuration sets.
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公开(公告)号：US20240404236A1
公开(公告)日：2024-12-05
申请号：US18008367
申请日：2021-12-08
Inventor： Wenhua HAN
Abstract: An object segmentation method includes: generating and inputting a frame to be identified, a previous frame of the frame to be identified and a reference frame based on a video to be identified into an encoding network to generate a feature map of the frame to be identified, a target object feature map of the reference frame and a target object feature map of the previous frame; generating a first correlation matrix and a second correlation matrix; generating a first correlation feature map and a second correlation feature map; and generating an object segmentation image corresponding to a current frame based on the feature map of the frame to be identified.
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Patent Agency Ranking
公开(公告)号：US12158839B2
公开(公告)日：2024-12-03
申请号：US17454900
申请日：2021-11-15
Abstract: The disclosure provides a method and an apparatus for allocating memory, and an electronic device. Multiple frames of speech data are received and input to a neural network model. The neural network model is configured to ask for multiple data tensors when processing the multiple frames of speech data, and the multiple data tensors share a common memory.
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公开(公告)号：US12147247B2
公开(公告)日：2024-11-19
申请号：US17884136
申请日：2022-08-09
Inventor： Haodong Ding , Liangjun Zhang
IPC: G05D1/00
Abstract: Provided are a vehicle attitude estimation method, an electronic device and a storage medium, relates to a technical field of data processing, and in particular to fields of automatic driving, intelligent transportation, Internet of Things, big data and the like. A specific implementation solution includes: obtaining first target data, based on point cloud data of a vehicle, the first target data being capable of constituting a target surface of the vehicle; performing attitude estimation on a target body for surrounding the vehicle, based on the first target data, to obtain an estimation result; and estimating an attitude of the vehicle, based on the estimation result. According to the implementation solution, precise or accurate estimation of the attitude of the vehicle may be achieved.
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公开(公告)号：US20240371259A1
公开(公告)日：2024-11-07
申请号：US18393376
申请日：2023-12-21
Inventor： Yixiong XIAO , Hao YUAN , Jingbo ZHOU
IPC: G08G1/01
Abstract: Provided is a source tracing method for traffic congestion, an electronic device and a storage medium, relating to the field of smart transportation, traffic management, traffic information processing and other technologies. The method includes: determining an undetermined road section and at least two reference road sections related to the undetermined road section from a target road network; obtaining a congestion infection distance between the undetermined road section and the reference road section within a target period; calculating a congestion time difference between a first congestion moment of the undetermined road section within the target period and a second congestion moment of the reference road section within the target period; and determining the undetermined road section as a congestion source of the target road network within the target period when determining that a correlation between the congestion infection distance and the congestion time difference meets a preset correlation requirement.
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公开(公告)号：US20240370719A1
公开(公告)日：2024-11-07
申请号：US18512766
申请日：2023-11-17
Inventor： Congxi XIAO , Jizhou HUANG , Jingbo ZHOU
Abstract: This disclosure provides a data generation method, model training method, electronic device, and medium. The data generation method includes: obtaining urban graph data, the urban graph data including a node set, an edge set and a feature set, wherein the node set includes a central node corresponding to a predetermined urban entity, the edge set includes a neighborhood corresponding to the central node, the neighborhood includes other nodes in the node set connected to the central node via an edge, and the feature set includes features of nodes in the node set; partitioning a target region into at least two sub-regions to obtain a region partition set; obtaining a regional feature of each sub-region by aggregating features corresponding to all nodes in the sub-region; and updating a feature of the central node based on the regional features of the sub-regions in the region partition set to obtain target feature data.
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公开(公告)号：US20240370485A1
公开(公告)日：2024-11-07
申请号：US18748078
申请日：2024-06-19
Inventor： Chenchang ZHU , Jialin FENG
IPC: G06F16/435 , G06F16/438
Abstract: The present disclosure provides a vector retrieval method and apparatus, a device and a medium, and relates to the field of artificial intelligence technologies, particularly the fields of cloud computing technologies, big data technologies, or the like. The vector retrieval method includes: acquiring a plurality of candidate vector indexes generated in advance, the plurality of candidate vector indexes being generated based on a plurality of candidate field values included in a target field of original data; acquiring a query vector and a filter condition, the filter condition being used for indicating a condition required to be satisfied by a target vector corresponding to the query vector; if the filter condition includes a target field value required to be satisfied by the target field, determining a target vector index corresponding to the target field value in the plurality of candidate vector indexes; and performing query in the target vector index based on the query vector to obtain the target vector.
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