METHOD OF PREPROCESSING IMAGE INCLUDING BIOLOGICAL INFORMATION
    11.
    发明申请
    METHOD OF PREPROCESSING IMAGE INCLUDING BIOLOGICAL INFORMATION 审中-公开
    预处理包括生物信息的图像的方法

    公开(公告)号:US20160364624A1

    公开(公告)日:2016-12-15

    申请号:US15049529

    申请日:2016-02-22

    CPC classification number: G06K9/00067 G06K9/3241

    Abstract: A method of preprocessing an image including biological information is disclosed, in which an image preprocessor may set an edge line in an input image including biological information, calculate an energy value corresponding to the edge line, and adaptively crop the input image based on the energy value.

    Abstract translation: 公开了一种预处理包括生物信息的图像的方法,其中图像预处理器可以在包括生物信息的输入图像中设置边缘线,计算与边缘线相对应的能量值,并且基于能量自适应地裁剪输入图像 值。

    METHOD AND APPARATUS FOR FACIAL RECOGNITION
    12.
    发明申请
    METHOD AND APPARATUS FOR FACIAL RECOGNITION 审中-公开
    方法和装置用于真实识别

    公开(公告)号:US20160042223A1

    公开(公告)日:2016-02-11

    申请号:US14795002

    申请日:2015-07-09

    Abstract: At least some example embodiments disclose a method and apparatus for facial recognition. The facial recognition method includes detecting initial landmarks from a facial image, first normalizing the facial image using the initial landmarks, updating a position of at least one of intermediate landmarks based on the first normalizing, the intermediate landmarks being landmarks transformed from the initial landmarks through the first normalizing, second normalizing the facial image after the updating and recognizing a face using a feature of the second normalized facial image.

    Abstract translation: 至少一些示例性实施例公开了用于面部识别的方法和装置。 面部识别方法包括从面部图像检测初始界标,首先使用初始地标标准化面部图像,基于第一归一化来更新中间地标中的至少一个的位置,中间地标是从初始地标变换的地标,通过 第一归一化,使用第二标准化脸部图像的特征更新并识别脸部之后,对面部图像进行二次归一化。

    METHOD AND APPARATUS WITH RECOGNITION MODEL TRAINING

    公开(公告)号:US20230143874A1

    公开(公告)日:2023-05-11

    申请号:US17978425

    申请日:2022-11-01

    CPC classification number: G06V10/774 G06V10/7715 G06V10/82

    Abstract: A processor-implemented method includes: generating a first sample image and a second sample image by performing data augmentation on an input training image; generating a first feature map of the first sample image and a second feature map of the second sample image by performing feature extraction on the first sample image and the second sample image using an encoding model; determining first loss data according to a relationship between first feature vectors of the first feature map and second feature vectors of the second feature map; estimating relative geometric information of the first feature map and the second feature map using a relationship estimation model; determining second loss data according to the relative geometric information, based on label data according to a geometric arrangement of the first sample image and the second sample image in the input training image; and training the encoding model and the relationship estimation model, based on the first loss data and the second loss data.

    METHOD AND APPARATUS WITH GENERATION OF TRANSFORMED IMAGE

    公开(公告)号:US20220148244A1

    公开(公告)日:2022-05-12

    申请号:US17344114

    申请日:2021-06-10

    Abstract: A method with generation of a transformed image includes: receiving an input image; extracting, from the input image, coefficients corresponding to semantic elements of the input image; selecting at least one first target coefficient, among the coefficients, corresponding to at least one target semantic element that is to be changed among the semantic elements of the input image; changing the at least one first target coefficient; and generating a transformed image from the input image by applying the coefficients, including the changed at least one first target coefficient, to basis vectors used to represent the semantic elements of the input image in an embedding space of a neural network, the basis vectors corresponding to the semantic elements of the input image.

    IMAGE PROCESSING APPARATUS AND METHOD

    公开(公告)号:US20210118095A1

    公开(公告)日:2021-04-22

    申请号:US16910406

    申请日:2020-06-24

    Abstract: An image processing method includes extracting a first region in a first image by inputting the first image to a pretrained neural network, upscaling a resolution of the first region by performing neural network-based super resolution processing on the first region, and upscaling a resolution of a second region in the first image from which the first region is excluded by performing interpolation on the second region.

    METHOD AND APPARATUS FOR EXTRACTING FEATURE FROM INPUT IMAGE

    公开(公告)号:US20190138792A1

    公开(公告)日:2019-05-09

    申请号:US16234720

    申请日:2018-12-28

    Abstract: At least one example embodiment discloses a method of extracting a feature from an input image. The method may include detecting landmarks from the input image, detecting physical characteristics between the landmarks based on the landmarks, determining a target area of the input image from which at least one feature is to be extracted and an order of extracting the feature from the target area based on the physical characteristics and extracting the feature based on the determining.

    MULTI-MODAL FUSION METHOD FOR USER AUTHENTICATION AND USER AUTHENTICATION METHOD
    20.
    发明申请
    MULTI-MODAL FUSION METHOD FOR USER AUTHENTICATION AND USER AUTHENTICATION METHOD 审中-公开
    用户认证和用户认证方法的多模式融合方法

    公开(公告)号:US20170039357A1

    公开(公告)日:2017-02-09

    申请号:US15097555

    申请日:2016-04-13

    Abstract: A user authentication method includes receiving a first input image including information on a first modality; receiving a second input image including information on a second modality; determining at least one first score by processing the first input image based on at least one first classifier, the at least one first classifier being based on the first modality; determining at least one second score by processing the second input image based on at least one second classifier, the at least one second classifier being based on the second modality; and authenticating a user based on the at least one first score, the at least one second score, a first fusion parameter of the at least one first classifier, and a second fusion parameter of the at least one second classifier.

    Abstract translation: 用户认证方法包括接收包括关于第一模态的信息的第一输入图像; 接收包括关于第二模态的信息的第二输入图像; 通过基于至少一个第一分类器处理所述第一输入图像来确定至少一个第一分数,所述至少一个第一分类器基于所述第一模态; 通过基于至少一个第二分类器处理所述第二输入图像来确定至少一个第二分数,所述至少一个第二分类器基于所述第二模态; 以及基于所述至少一个第一分数,所述至少一个第二分数,所述至少一个第一分类器的第一融合参数和所述至少一个第二分类器的第二融合参数来验证用户。

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