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公开(公告)号：US20200207351A1
公开(公告)日：2020-07-02
申请号：US16726900
申请日：2019-12-25
Inventor： Nan WU
Abstract: The present application provides a method and an apparatus for testing a ramp driving performance, and a storage medium, where the method includes: controlling, according to a preset traveling track, an automatic driving vehicle to perform a stopping operation when the automatic driving vehicle is traveling on a ramp to a reference position; obtaining relative position information between an actual stopping position of the automatic driving vehicle and a reference object disposed at the reference position; and determining, according to the relative position information, whether the automatic driving vehicle is accurately stopped on the ramp. In the technical solution, the driving performance of the automatic driving vehicle in a special scenario such as ramp stopping can be accurately detected, thereby ensuring a driving safety of the automatic driving vehicle in the ramp stopping scenario.
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公开(公告)号：US20200184824A1
公开(公告)日：2020-06-11
申请号：US16704005
申请日：2019-12-05
Inventor： Fan YANG , Fan ZHU , Weicheng ZHU , Leibing LV , Lin MA
Abstract: The present disclosure provides a method, an apparatus, a device and a readable storage medium for planning a pass path. The method includes: acquiring current road environment information in front of a vehicle; setting pass candidate points according to the current road environment information and a driving strategy; and determining a current optimal passable path according to the pass candidate points. Since the pass candidate points are set according to the current road environment information and the driving strategy, and the current optimal passable path is determined according to the pass candidate points, thereby effectively decreasing the calculation amount of the impassable path calculation in prior art due to direct setting of pass candidate points in all areas in front of an unmanned vehicle.
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公开(公告)号：US20200183401A1
公开(公告)日：2020-06-11
申请号：US16703999
申请日：2019-12-05
Inventor： Fan Yang , Fan Zhu , Weicheng Zhu , Leibing Lv , Lin Ma , Ning Yu , Bei Liu
Abstract: Provided are a pass route planning method and apparatus, a device and a readable storage medium. The method includes: obtaining current road environment information in front of a vehicle; determining a current passable area according to the current road environment information; setting pass candidate points in the current passable area; and determining a current optimal passable route according to the pass candidate points. Firstly, the passable area is determined, and then the pass candidate points are set in the passable area, and thus the current optimal passable route is calculated according to the pass candidate points in the passable area, which can effectively reduce a calculation amount of unreachable pass routes in the prior art in which candidate points are set in all areas directly in front of an unmanned vehicle, thereby reducing a calculation amount for planning a pass route and improving a planning speed of the pass route.
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304.发明申请公开(公告)号：US20190317686A1
公开(公告)日：2019-10-17
申请号：US16456454
申请日：2019-06-28
Inventor： Jingwei MA
Abstract: A method, an apparatus, a device, and a storage medium for processing a data location of a storage device. The method includes: when a device is restarted, writing a first location information set of historical data stored in the storage device into a memory, where the historical data and location information corresponding to the historical data are stored in the storage device correspondingly; if there is update data in the storage device, writing location information of the update data stored corresponding to the update data in the storage device into the memory; and generating, according to the first location information set and the location information of the update data, a second location information set in the memory, and storing the second location information into the storage device.
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公开(公告)号：US20190206236A1
公开(公告)日：2019-07-04
申请号：US16136195
申请日：2018-09-19
Inventor： SHENG TAO , HUO CAO , ZESHU SHEN , HAISONG WANG , JI TAO , DEWANG SONG
CPC classification number: G08G1/0145 , G05D1/0088 , G05D1/0276 , G05D2201/0213 , G08G1/08 , G08G1/087 , G08G1/0968 , H04W4/44
Abstract: Provided are a method, an apparatus and a device for controlling a cooperative intersection. The method includes: receiving a passage request for intersection transmitted by a first vehicle, the passage request for intersection comprises vehicle information of the first vehicle; transmitting a traffic directing instruction to the first vehicle according to the vehicle information of the first vehicle to cause the first vehicle pass the intersection according to the traffic directing instruction. The passage request for intersection of the host vehicle is received through a traffic control unit, and a traffic directing instruction is transmitted to the host vehicle according to the vehicle information of the host vehicle in the intersection request. The traffic directing instruction is transmitted through V2X communication, which can finely direct the driving lane, follow-up driving, passage time, stop time and stop location for each vehicle, thereby making the intersection traffic safer and more efficient.
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Patent Agency Ranking
公开(公告)号：US12298956B2
公开(公告)日：2025-05-13
申请号：US18748362
申请日：2024-06-20
Inventor： Chenchang Zhu , Jialin Feng
IPC: G06F16/22 , G06F16/2453
Abstract: A method for generating an index, and an electronic device are provided. The detailed solution includes: determining a first parameter group and a second parameter group in response to receiving a query request for a first vector database and there being no available index for the first vector database, constructing a first index for the first vector database based on the first parameter group, and querying the first vector database based on the first index; constructing a second index for the first vector database based on the second parameter group in response to meeting a preset condition; and in response to determining that construction of the second index is completed, deleting the first index, and querying the first vector database based on the second index.
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公开(公告)号：US20250149110A1
公开(公告)日：2025-05-08
申请号：US18929408
申请日：2024-10-28
Inventor： Kunrui Zhu , Lihang Liu , Xiaomin Fang , Xiaonan Zhang , Jingzhou He
Abstract: A method for predicting a structure of a protein complex includes: obtaining an initial coordinate of each amino acid residue in a target protein complex, and obtaining a target residue pair feature, a first multiple sequence alignment (MSA) feature and a second MSA feature of each protein monomer in the target protein complex; and inputting the initial coordinate of each amino acid residue, and the target residue pair feature, the first MSA feature and the second MSA feature of each protein monomer into an N-level fold iteration network layer, and obtaining a target coordinate of each amino acid residue by predicting a torsion angle, a position transformation at residue level and a position transformation at monomer chain level of each amino acid residue via the N level fold iteration network layer, to obtain a predicted structure of the protein complex.
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公开(公告)号：US12283085B2
公开(公告)日：2025-04-22
申请号：US17902323
申请日：2022-09-02
Inventor： Siqi Xu , Ke Sun , Jian Gong , Xu Pan , Zhiqun Xia , Zhe Yang , Zecheng Zhuo
IPC: G06V10/762 , G06F16/28 , G06V10/74 , G06V10/764
Abstract: Provided is a data labeling method based on artificial intelligence, an apparatus, and a storage medium relating to the field of artificial intelligence, particularly data labeling, image recognition, and natural language processing. The method includes: determining a plurality of samples involved in clustering; performing a plurality of following operations circularly to realize iterative processing, until a convergence condition is satisfied or a quantity of iterations reaches a number threshold, comprising: pre-clustering the plurality of samples according to a vector representation of the respective samples to obtain a plurality of class clusters, each class cluster containing at least one sample; receiving labeling information for the respective class clusters and re-determining the plurality of samples according to the labeling information; and determining a clustering result according to the labeling information for the respective class clusters.
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309.发明申请公开(公告)号：US20250124679A1
公开(公告)日：2025-04-17
申请号：US18748082
申请日：2024-06-19
Inventor： Lei WANG , Xiaodong ZHANG , Shiyan LI
Abstract: The present disclosure provides method and apparatus for transferring facial expression of digital human, electronic device, and storage medium, which relates to the fields of augmented reality technologies, virtual reality technologies, computer vision technologies, deep learning technologies, or the like, and can be applied to scenarios, such as metaverse, a virtual digital human, or the like, An implementation includes: screening an identification of a target reference model matched with an object model from a preset reference model library; the reference model library including a plurality of reference models; acquiring an expression library of the target reference model based on the identification of the target reference model; and transferring a last frame of an expression in the expression library of the target reference model into the object model to obtain a last frame of an expression of the object model.
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公开(公告)号：US12277398B2
公开(公告)日：2025-04-15
申请号：US17694034
申请日：2022-03-14
Inventor： Jian Gong , Yu Sun , Hao Tian , Hua Wu , Haifeng Wang , Qiaoqiao She
IPC: G06F40/40 , G06F40/205 , G06F40/284
Abstract: A model training method, a model training platform, an electronic device and a storage medium are provided, which can be used in the field of artificial intelligence, particularly the fields of natural language processing and deep learning. The model training method includes: receiving an input; determining, based on the input, a user-oriented prefabricated function; determining, based on the input, a model training function; determining, based on the input, a pre-trained model; determining, based on the input, a network structure associated with the pre-trained model so as to support use of the pre-trained model; training, based on the input, the model by using the prefabricated function, the model training function, and the pre-trained model; and providing an output associated with a trained model.
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