QUANTUM STATE PROCESSING METHOD, COMPUTING DEVICE AND STORAGE MEDIUM

    公开(公告)号:US20230244974A1

    公开(公告)日:2023-08-03

    申请号:US17929575

    申请日:2022-09-02

    Inventor: Kun FANG Xin WANG

    CPC classification number: G06N10/20 G06N10/80

    Abstract: A quantum state processing method, a computing device and a storage medium. The method includes: acquiring a first group of measurement results for a first quantum state ρ, the first group of measurement results including a measurement result for the first quantum state ρ and a measurement result for an approximate n-order quantum state ρ[n]; acquiring a second group of measurement results for a second quantum state σ, the second group of measurement results including a measurement result for the second quantum state σ and a measurement result for an approximate m-order quantum state σ[m]; obtaining, based on at least the first group of measurement results and the second group of measurement results, a target high-order inner product tr(ρnσm) for the first quantum state ρ and the second quantum state σ; and the ρn characterizing an n-order quantum state of the first quantum state σ.

    CAMERA EXTRINSIC PARAMETER CORRECTION METHOD AND APPARATUS, AND STORAGE MEDIUM

    公开(公告)号:US20230230392A1

    公开(公告)日:2023-07-20

    申请号:US18054773

    申请日:2022-11-11

    CPC classification number: G06V20/588 G06T7/80

    Abstract: A camera extrinsic parameter correction method includes acquiring multiple road surface images continuous in time and performing classification to obtain a mutated image and a time-adjacent image corresponding to the mutated image; determining a matching point pair from pixel points of the mutated image and pixel points of the corresponding time-adjacent image and determining a target view angle point pair of the matching point pair in a target view angle; and correcting a camera extrinsic parameter corresponding to the mutated image according to the difference between two target view angle points in the target view angle point pair, where the camera extrinsic parameter is configured for conversion of a pixel point in a current view angle into a pixel point in the target view angle.

    METHOD, ELECTRONIC DEVICE, AND STORAGE MEDIUM FOR DETERMINING PROMPT VECTOR OF PRE-TRAINED MODEL

    公开(公告)号:US20230222344A1

    公开(公告)日:2023-07-13

    申请号:US18118859

    申请日:2023-03-08

    CPC classification number: G06N3/082

    Abstract: A method for determining a prompt vector of a pre-trained model, includes: obtaining a first one of prompt vectors and a first vector corresponding to sample data; obtaining N pruned models by N different pruning processing on the pre-trained model, where N is any integer greater than 1; obtaining a first score corresponding to the first one of the prompt vectors by fusing the first vector and the first one of the prompt vectors and inputting the fused first vector and first one of the prompt vectors into the N pruned models respectively; determining a second one of the prompt vectors by modifying, based on the first score, the first one of the prompt vectors; and based on the second one of the prompt vectors, returning to obtaining the first score until determining a target prompt vector corresponding to the sample data.

    Video Title Generation Method, Device, Electronic Device and Storage Medium

    公开(公告)号:US20230222161A1

    公开(公告)日:2023-07-13

    申请号:US18049160

    申请日:2022-10-24

    CPC classification number: G06F16/7844 G06F40/279 G06V30/153

    Abstract: Provided are a video title generation method, an electronic device and a storage medium, which relate to a technical field of video, and in particular to a technical field of short video. The method includes: obtaining a plurality of pieces of optional text information, for a first video file; determining central text information, from the plurality of pieces of optional text information, the central text information being optional text information with the highest similarity to content of the first video file; and determining the central text information as a title of the first video file. That is, an interest point in an original video file can be determined according to user's interactive behavior data on the original video file, and the original video file can be clipped based on the interest point to obtain a plurality of clipped video files, namely, short videos.

    PRODUCT RECOGNITION METHOD, MODEL TRAINING METHOD, DEVICE AND ELECTRONIC DEVICE

    公开(公告)号:US20230214985A1

    公开(公告)日:2023-07-06

    申请号:US18181967

    申请日:2023-03-10

    CPC classification number: G06T7/0004 G06T2207/20081

    Abstract: A product recognition method and device, a model training method and device, and an electronic device are provided. The product recognition method includes: obtaining image data of a product; performing defect recognition on the image data based on a first recognition model, to obtain a first recognition result, wherein the first recognition model is configured to recognize a defective product; performing qualification recognition on the image data based on a second recognition model to obtain a second recognition result, wherein the second recognition model is configured to recognize a qualified product; determining a target recognition result of the product based on the first recognition result and the second recognition result.

    METHOD OF UPDATING ROAD INFORMATION, ELECTRONIC DEVICE, AND STORAGE MEDIUM

    公开(公告)号:US20230213353A1

    公开(公告)日:2023-07-06

    申请号:US18183003

    申请日:2023-03-13

    CPC classification number: G01C21/3815 G06T7/10 G06T5/002

    Abstract: A method of updating a road information, an electronic device, and a storage medium, which relate to an artificial intelligence technology field, in particular to fields of computer vision, deep learning, big data, high-definition map, intelligent transportation, automatic driving and autonomous parking, cloud service, Internet of Vehicles and intelligent cabin technologies. The method includes: processing image data corresponding to a target road region to obtain a set of first road lines; obtaining a set of second road lines according to a trajectory map corresponding to the target road region; calibrating the set of first road lines by using the set of second road lines to obtain a set of third road lines; combining the set of third road lines and a set of historical road lines corresponding to the target road region to obtain a combination result; and updating the set of historical road lines according to the combination result.

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