TESTING METHOD AND DEVICE OF AUTONOMOUS VEHICLE, ELECTRONIC APPARATUS, AND MEDIUM

    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.

    METHOD FOR TRAINING CLASSIFICATION MODEL, CLASSIFICATION METHOD, APPARATUS AND DEVICE

    公开(公告)号:US20210312288A1

    公开(公告)日:2021-10-07

    申请号:US17349280

    申请日:2021-06-16

    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.

    KEYWORD GENERATING METHOD, APPARATUS, DEVICE AND STORAGE MEDIUM

    公开(公告)号:US20210303608A1

    公开(公告)日:2021-09-30

    申请号:US17347448

    申请日:2021-06-14

    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.

    TRAINING METHOD AND APPARATUS OF POI RECOMMENDATION MODEL OF INTEREST POINTS, AND ELECTRONIC DEVICE

    公开(公告)号:US20210302185A1

    公开(公告)日:2021-09-30

    申请号:US17347418

    申请日:2021-06-14

    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.

    METHOD AND APPARATUS FOR VEHICLE RE-IDENTIFICATION, TRAINING METHOD AND ELECTRONIC DEVICE

    公开(公告)号:US20210287015A1

    公开(公告)日:2021-09-16

    申请号:US17336641

    申请日:2021-06-02

    Abstract: The present application discloses a method and an apparatus for vehicle re-identification, a training method, an electronic device and a storage medium, relating to the field of artificial intelligence, in particular, to technologies of computer vision, deep learning and intelligent transport. A specific implementation is: acquiring a picture of a target vehicle to be re-identified, determining a target two-dimensional image of the target vehicle based on the picture and a preset initial three-dimensional model, the initial three-dimensional model being generated based on sample three-dimensional information of a sample vehicle, and re-identifying the target two-dimensional image to generate and output an identification result.

    POSITION DETECTING METHOD, DEVICE AND STORAGE MEDIUM FOR VEHICLE LADAR

    公开(公告)号:US20210263138A1

    公开(公告)日:2021-08-26

    申请号:US17240142

    申请日:2021-04-26

    Inventor: Nan WU

    Abstract: The present application provides a position detecting method, device and storage medium for a vehicle ladar, where the method includes: detecting, through a ladar disposed on an autonomous vehicle, detection data of at least one wall of an interior room in which the autonomous vehicle is located, obtaining a point cloud image according to the detection data of the at least one wall, and judging, according to the point cloud image, whether an installation position of the ladar is accurate. According to the technical solution, it is possible to accurately detect whether the installation position of the ladar is accurate, provide a prerequisite for calibration of the installation position of the ladar, and improve detection accuracy of the ladar for obstacles around the autonomous vehicle.

    FILTER DEBUGGING METHOD, DEVICE, ELECTRONIC APPARATUS AND READABLE STORAGE MEDIUM

    公开(公告)号:US20210211365A1

    公开(公告)日:2021-07-08

    申请号:US17207571

    申请日:2021-03-19

    Abstract: A filter debugging method, a device, an electronic apparatus and a readable storage medium are provided. The filter debugging method includes: step S1: inputting a current hole parameter and a current index value of a filter into a policy network which is pre-trained; step S2: determining, by the policy network, a target hole to be polished of the filter, according to the current hole parameter and the current index value of the filter; step S3: controlling a mechanical arm to polish the target hole of the filter; and step S4: determining whether the filter is qualified according to an index value of the polished filter; in a case that the filter is qualified, ending a process including the steps S1 to S4; in a case that the filter is unqualified, performing the steps S1 to S4 circularly until the filter is qualified.

    METHOD, APPARATUS, DEVICE, AND STORAGE MEDIUM FOR INTENTION RECOMMENDATION

    公开(公告)号:US20210209109A1

    公开(公告)日:2021-07-08

    申请号:US17207503

    申请日:2021-03-19

    Abstract: The present application discloses a method, an apparatus, a device, and a storage medium for intention recommendation, which relates to the field of big data, artificial intelligence, intelligent search, information flow and deep learning technologies in the field of computer technologies. A specific implementation scheme includes: receiving an intention query request carrying an intention keyword and a user identification, determining a first recommendation list according to the intention keyword and a pre-configured intention repository, where the intention repository includes at least one tree-shaped intention set, and each tree-shaped intention set includes at least one graded intention, processing intentions in the first recommendation list by using intention strategy information corresponding to the user identification to obtain a target recommendation list and output it.

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