Object recognition method and apparatus

    公开(公告)号:US12033369B2

    公开(公告)日:2024-07-09

    申请号:US17668101

    申请日:2022-02-09

    CPC classification number: G06V10/761 G06V10/40

    Abstract: A method for optimizing a photographing pose of a user, where the method is applied to an electronic device, and the method includes: displaying a photographing interface of a camera of the electronic device; obtaining a to-be-taken image in the photographing interface; determining, based on the to-be-taken image, that the photographing interface includes a portrait; entering a pose recommendation mode; and presenting a recommended human pose picture to a user in a predetermined preview manner, where the human pose picture is at least one picture that is selected from a picture library through metric learning and that has a top-ranked similarity to the to-be-taken image, and where the similarity is an overall similarity obtained by fusing a background similarity and a foreground similarity.

    MODEL DISTILLATION METHOD AND RELATED DEVICE
    33.
    发明公开

    公开(公告)号:US20240185086A1

    公开(公告)日:2024-06-06

    申请号:US18443052

    申请日:2024-02-15

    CPC classification number: G06N3/096 G06N3/045

    Abstract: This disclosure relates to the field of artificial intelligence, and provides model distillation methods and apparatuses. In an implementation, a method including: obtaining first input data and second input data from a second computing node, wherein the first input data is output data of the third sub-model, and the second input data is output data processed by the fourth sub-model, processing the first input data by using the first sub-model, to obtain a first intermediate output, processing the second input data by using the second sub-model, to obtain a second intermediate output, wherein the first intermediate output and the second intermediate output are used to determine a first gradient, and distilling the first sub-model based on the first gradient, to obtain an updated first sub-model.

    Content explanation method and apparatus

    公开(公告)号:US11574203B2

    公开(公告)日:2023-02-07

    申请号:US16586092

    申请日:2019-09-27

    Abstract: A content explanation method and apparatus applied to content explanation includes identifying, by a content explanation apparatus, an emotion of the user, when identifying a negative emotion showing that the user is confused about delivered multimedia information, obtaining, by the content explanation apparatus, a target representation manner of target content in a target intelligence type, where the target content is content about which the user is confused in the multimedia information delivered to the user by an information delivery apparatus associated with the content explanation apparatus, and presenting, by the content explanation apparatus, the target content to the user in the target representation manner.

    VOICE INTERACTION METHOD AND ELECTRONIC DEVICE

    公开(公告)号:US20230017274A1

    公开(公告)日:2023-01-19

    申请号:US17952401

    申请日:2022-09-26

    Abstract: Embodiments of this application provide a voice interaction method and an electronic device, and relate to the field of artificial intelligence AI technologies and the field of voice processing technologies. A specific solution includes: An electronic device may receive first voice information sent by a second user, and the electronic device recognizes the first voice information in response to the first voice information. The first voice information is used to request a voice conversation with a first user. The electronic device may have, on a basis that the electronic device recognizes that the first voice information is voice information of the second user, a voice conversation with the second user by imitating a voice of the first user and in a mode in which the first user has a voice conversation with the second user.

    Touchscreen device and method and apparatus for performing operation

    公开(公告)号:US11520427B2

    公开(公告)日:2022-12-06

    申请号:US17122620

    申请日:2020-12-15

    Inventor: Li Qian

    Abstract: Embodiments of the present invention disclose a touchscreen device, and a method and an apparatus for performing an operation that relate to the field of information technologies, so as to reduce a limitation of identifiable operations provided to a user, and improve user experience. The method includes: detecting, by a touchscreen device, pressing force track information of a user on a touchscreen, where the pressing force track information is used to represent a change of a pressing force level in a process in which the user continuously presses the touchscreen; determining an operation corresponding to the pressing force track information, according to a current touch operation application scenario and correspondences between pressing force track information and operations; and performing the operation. The present invention is applicable to a touchscreen device that determines a corresponding operation according to pressing force track information of a user and performs the operation.

    SPEECH EMOTION RECOGNITION METHOD AND APPARATUS

    公开(公告)号:US20220036916A1

    公开(公告)日:2022-02-03

    申请号:US17451061

    申请日:2021-10-15

    Abstract: A plurality of pieces of emotional state information corresponding to a plurality of speech frames in a current utterance are obtained based on a first neural network model; statistical operation is performed on the plurality of pieces of emotional state information, to obtain a statistical result, and then the emotional state information corresponding to the current utterance is obtained based on a second neural network device, the statistical result corresponding to the current utterance, and statistical results corresponding to a plurality of utterances before the current utterance.

    Recommendation Model Training Method and Related Apparatus

    公开(公告)号:US20210326729A1

    公开(公告)日:2021-10-21

    申请号:US17360581

    申请日:2021-06-28

    Abstract: A recommendation model training method includes selecting a positive sample in a sample set, and adding the positive sample to a training set, where the sample set includes the positive sample and negative samples, each sample includes n sample features, n≥1, and the sample features of each sample include a feature used to represent whether the sample is a positive sample or a negative sample, calculating sampling probabilities of the negative samples in the sample set by using a preset algorithm, selecting a negative sample from the sample set based on the sampling probability, and adding the negative sample to the training set, and performing training by using the samples in the training set, to obtain a recommendation model.

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