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公开(公告)号：US20220004811A1
公开(公告)日：2022-01-06
申请号：US17479061
申请日：2021-09-20
Inventor： Ruoyu GUO , Yuning DU , Weiwei LIU , Xiaoting YIN , Qiao ZHAO , Qiwen LIU , Ran BI , Xiaoguang HU , Dianhai YU , Yanjun MA
IPC: G06K9/62
Abstract: There is provided a method and apparatus of training a model, a device, and a medium, which relate to artificial intelligence, and in particular to a deep learning and image processing technology. The method may include: determining a plurality of augmented sample sets associated with a plurality of original samples; determining a first constraint according to a first model based on the plurality of augmented sample sets; determining a second constraint according to the first model and a second model based on the plurality of augmented sample sets, wherein the second constraint is associated with a difference between outputs of the first model and the second model for one augmented sample, and the first model has a complexity lower than that of the second model; training the first model based on at least the first constraint and the second constraint, so as to obtain a trained first model.
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公开(公告)号：US20210406981A1
公开(公告)日：2021-12-30
申请号：US17036155
申请日：2020-09-29
Inventor： Jiamei KANG , Shengran CHE , Hanyao SHAO
Abstract: The present disclosure discloses a method and apparatus of determining a display page, an electronic device and a medium, which relates to a field of information recommendation and may be used in fields of deep learning, cloud computing and cloud service. The specific implementation scheme includes: acquiring attribute information of a user, wherein the attribute information includes position information; determining, based on the position information, at least one first information category for the user in a preset first information dimension; acquiring recommendation information classified into each first information category of the at least one first information category; and determining the display page for the user based on the preset first information dimension, the at least one first information category, and the recommendation information classified into the each first information category.
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273.发明申请公开(公告)号：US20210406579A1
公开(公告)日：2021-12-30
申请号：US17468848
申请日：2021-09-08
Inventor： Tianwei Lin , Dongliang He , Fu Li
Abstract: The present disclosure provides a model training method, an identification method, device, storage medium and program product, relating to computer vision technology and deep learning technology. In the solution provided by the present application, the image is deformed by the means of deforming the first training image without label itself, and the first unsupervised identification result is obtained by using the first model to identify the image before deformation, and the second unsupervised identification result is obtained by using the second model to identify the image after deformation, and the first unsupervised identification result of the first model is deformed, thus a consistency loss function can be constructed according to the second unsupervised identification result and the scrambled identification result. In this way, it is able to enhance the constraint effect of the consistency loss function and avoid destroying the scene semantic information of the images used for training.
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274.发明申请公开(公告)号：US20210406067A1
公开(公告)日：2021-12-30
申请号：US17184723
申请日：2021-02-25
Inventor： He QI , Yazhi WANG
Abstract: The present disclosure provides a distributed storage method, involving the technical fields of computer and cloud computing, and including: reading and sending data to an external shuffle service in response to a request of a task from a driver thread; modifying a state of the task to a waiting-for-completion state after finishing sending the data to the external shuffle service; and sending the waiting-for-completion state to the driver thread, to cause the driver thread to release an executor thread corresponding to the task. The distributed storage method can reduce the waste of the resources of the executor thread and improves the efficiency of task operations. The present disclosure also provides an electronic apparatus, and a non-transitory computer-readable storage medium.
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公开(公告)号：US20210403011A1
公开(公告)日：2021-12-30
申请号：US17185733
申请日：2021-02-25
Inventor： Jun ZHAO
Abstract: The present disclosure provides a testing method of an autonomous vehicle. The method includes: acquiring test data about a test site generated during a testing process, wherein the test data includes a corresponding relationship between a current cumulative number of problems monitored during the testing process and a current mileage of the autonomous vehicle; determining a corresponding relationship between a problem monitoring ratio and the current mileage based on the test data, wherein the problem monitoring ratio includes a ratio of the current cumulative number of problems monitored to a total number of problems monitored; and performing fitting on a preset evaluation model based on the corresponding relationship between the problem monitoring ratio and the current mileage, so as to obtain an optimized evaluation model, wherein the optimized evaluation model is configured to evaluate a corresponding relationship between the problem monitoring ratio and a test mileage about the test site.
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Patent Agency Ranking
276.发明申请公开(公告)号：US20210390133A1
公开(公告)日：2021-12-16
申请号：US17207179
申请日：2021-03-19
Inventor： QIAOYI LI , XIANGKAI HUANG , YULIN LI , JU HUANG , XIAMENG QIN , DUOHAO QIN , MINGHAO LIU , JUNYU HAN
IPC: G06F16/583 , G06F16/532 , G06F16/93
Abstract: Disclosed are a method, apparatus and electronic device for annotating information of a structured document. A specific implementation is: obtaining a template image of a structured document and at least one piece of annotation information of a field to be filled in the template image, where the annotation information includes attribute value and historical content of the field to be filled, and historical position of the field to be filled in the template image; generating, according to the attribute value of the field to be filled, the historical content of the field to be filled and the historical position of the field to be filled in the template image, target filling information of the field to be filled; obtaining, according to the target filling information of the field to be filled, an image of an annotated structured document.
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公开(公告)号：US20210335127A1
公开(公告)日：2021-10-28
申请号：US17366637
申请日：2021-07-02
Inventor： Yuan WANG , Jin ZHAO , Xing SU , Shewei DENG , Xiang YANG , Hao ZHOU , Jing YAN , Shenglin QIN , Xiaoliang CONG , Yaling ZHANG
Abstract: The present application discloses a traffic monitoring method, an apparatus, a device, and a storage medium, relates to fields of autonomous driving, intelligent transportation, big data. The specific implementation is: acquiring road condition information and/or vehicle state information collected by a terminal device, where the terminal device is at least one of an unmanned vehicle and an unmanned aerial vehicle; performing a data analysis on the road condition information and/or the vehicle state information, and identifying a traffic event. Through the above procedure, monitoring efficiency of the traffic state is improved.
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公开(公告)号：US20210312288A1
公开(公告)日：2021-10-07
申请号：US17349280
申请日：2021-06-16
Inventor： Yaqing Wang , Dejing Dou
Abstract: The present application discloses a method for training a classification model, a classification method, an apparatus and a device. A specific implementation is: acquiring behavior information of multiple users and personal basic information of the multiple users; where categories of at least part of users of the multiple users are known; inputting the personal basic information of the multiple users into a classification model to be trained to obtain feature information of the multiple users and predicted categories of users with known categories; and training the classification model to be trained according to the behavior information of the multiple users, the feature information of the multiple users, the predicted categories of the users with the known categories, and real categories of the users with the known categories, to obtain a trained classification model. The user categories determined by using the classification model are more accurate.
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公开(公告)号：US20210303608A1
公开(公告)日：2021-09-30
申请号：US17347448
申请日：2021-06-14
Inventor： KAICHUN YAO , CHUAN QIN , HENGSHU ZHU , CHAO MA , JINGSHUAI ZHANG
IPC: G06F16/332 , G06F40/20 , G06F16/335
Abstract: This application discloses a keyword generating method, an apparatus, a device and a storage medium, which relate to the field of natural language processing in the field of artificial intelligence. A specific implementation scheme includes: inputting a target text into a text processing model, obtaining a word sequence corresponding to the target text, and generating a semantic representation sequence corresponding to the word sequence; making prediction about each semantic representation vector in the semantic representation sequence respectively to obtain a prediction result; and if the prediction result indicates that a word corresponding to the semantic representation vector is capable of triggering a generation of a keyword, outputting the keyword based on the semantic representation vector and the prediction result. This method improves the accuracy of generating keywords.
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280.发明申请公开(公告)号：US20210302185A1
公开(公告)日：2021-09-30
申请号：US17347418
申请日：2021-06-14
Inventor： JINGBO ZHOU , HUI XIONG
Abstract: Disclosed are training method and apparatus of a point-of-interest POI recommendation model and an electronic device, relating to the technical fields of artificial intelligence and big data. A specific implementation solution is as follows: when training and generating the POI recommendation model, it is precisely because it is considered that preference information of a user on a POI and a relationship between POIs at different levels will affect the accuracy of a POI recommendation, so when training and generating the POI recommendation model, the preference information of the user on the POI and the relationship between the POIs at different levels are obtained first, and the POI recommendation model is trained and generated according to the preference information of the user on the POI and the relationship between the POIs at different levels, thereby improving the accuracy of the POI recommendation model.
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