OBJECT DETECTION
    512.
    发明申请

    公开(公告)号:US20220067375A1

    公开(公告)日:2022-03-03

    申请号:US17200445

    申请日:2021-03-12

    Abstract: A method includes: determining at least one typical object ratio from a first training data set by counting ratios of objects in training pictures of the first training data set; determining at least one picture scaling size based at least on the at least one typical object ratio; scaling the training pictures of the first training data set according to the at least one picture scaling size; obtaining a second training data set by slicing the scaled training pictures; training an object detection model using the second training data set; and performing object detection on a to-be-detected picture using the trained object detection model. The object detection method according to the embodiments of the present disclosure can be used to complete, without manual intervention, a task of detecting an extremely small object.

    METHOD FOR SEMANTIC RETRIEVAL, DEVICE AND STORAGE MEDIUM

    公开(公告)号:US20220027569A1

    公开(公告)日:2022-01-27

    申请号:US17493375

    申请日:2021-10-04

    Inventor: Zenan LIN Jiajun LU

    Abstract: A method for a semantic retrieval, a device and a storage medium are provided. The method may include: receiving query information, and performing sequence labeling on the query information based on a pre-constructed knowledge graph to obtain a sequence labeling result, where the sequence labeling result includes a predetermined information part of the knowledge graph and a semantic retrieval part; constructing a set of a candidate entity matching the sequence labeling result based on the knowledge graph; and performing sematic matching between an entity in the set of the candidate entity and the semantic retrieval part in the sequence labeling result to obtain a set of an entity having a semantic relevance higher than a preset threshold.

    Method for Training Object Detection Model, Object Detection Method and Related Apparatus

    公开(公告)号:US20220020175A1

    公开(公告)日:2022-01-20

    申请号:US17489991

    申请日:2021-09-30

    Abstract: An object detection model training method, object detection method and related apparatus, relate to the field of artificial intelligence technologies such as computer vision, deep learning. An implementation includes: obtaining training sample data including a first remote sensing image and position annotation information of an anchor box of a subject to be detected in the first remote sensing image, where the position annotation information includes angle information of the anchor box relative to a preset direction; obtaining an object feature map of the first remote sensing image based on an object detection model, performing object detection on the subject to be detected based on the object feature map to obtain an object bounding box, and determining loss information between the anchor box and the object bounding box based on the angle information; updating a parameter of the object detection model based on the loss information.

    METHOD FOR TRAINING MULTILINGUAL SEMANTIC REPRESENTATION MODEL, DEVICE AND STORAGE MEDIUM

    公开(公告)号:US20220019743A1

    公开(公告)日:2022-01-20

    申请号:US17318577

    申请日:2021-05-12

    Abstract: Technical solutions relate to the natural language processing field based on artificial intelligence. According to an embodiment, a multilingual semantic representation model is trained using a plurality of training language materials represented in a plurality of languages respectively, such that the multilingual semantic representation model learns the semantic representation capability of each language; a corresponding mixed-language language material is generated for each of the plurality of training language materials, and the mixed-language language material includes language materials in at least two languages; and the multilingual semantic representation model is trained using each mixed-language language material and the corresponding training language material, such that the multilingual semantic representation model learns semantic alignment information of different languages.

    METHOD AND APPARATUS FOR TRAINING NATURAL LANGUAGE PROCESSING MODEL, DEVICE AND STORAGE MEDIUM

    公开(公告)号:US20220019736A1

    公开(公告)日:2022-01-20

    申请号:US17211669

    申请日:2021-03-24

    Abstract: The present application discloses a method and apparatus for training a natural language processing model, a device and a storage medium, which relates to the natural language processing field based on artificial intelligence. An implementation includes: constructing training language material pairs of a coreference resolution task based on a preset language material set, wherein each training language material pair includes a positive sample and a negative sample; training the natural language processing model with the training language material pair to enable the natural language processing model to learn the capability of recognizing corresponding positive samples and negative samples; and training the natural language processing model with the positive samples of the training language material pairs to enable the natural language processing model to learn the capability of the coreference resolution task.

    NAVIGATION METHOD, ELECTRONIC DEVICE, AND STORAGE MEDIUM

    公开(公告)号:US20220011125A1

    公开(公告)日:2022-01-13

    申请号:US17481813

    申请日:2021-09-22

    Abstract: A navigation method, an electronic device, and a storage medium, which are related to a field of artificial intelligence, such as depth learning, maps, and navigation. The specific implementation scheme includes: obtaining a parking space located in an indoor parking lot in response to an operation acquired based on a map application, generating an indoor-outdoor navigation route in the map application by taking the parking space as a destination address in the indoor-outdoor navigation route, and navigating a vehicle driven by a user to the parking space according to the indoor-outdoor navigation route.

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