CONDUCTOR AND METHOD OF MANUFACTURING THE SAME
    21.
    发明申请
    CONDUCTOR AND METHOD OF MANUFACTURING THE SAME 有权
    导体及其制造方法

    公开(公告)号:US20170040566A1

    公开(公告)日:2017-02-09

    申请号:US15003845

    申请日:2016-01-22

    Abstract: A conductor includes a plurality of metal nanostructures having a circular cross-sectional shape, where each of the metal nanostructure is surrounded by an organic material having a thickness of less than or equal to about 0.5 nm. A method of manufacturing a conductor includes preparing a metal nanostructure having a polygonal cross-sectional shape, and providing a metal nanostructure having a circular cross-sectional shape by supplying light to the metal nanostructure having a polygonal cross-sectional shape.

    Abstract translation: 导体包括具有圆形横截面形状的多个金属纳米结构,其中每个金属纳米结构被厚度小于或等于约0.5nm的有机材料包围。 制造导体的方法包括制备具有多边形横截面形状的金属纳米结构,并通过向具有多边形横截面形状的金属纳米结构提供光来提供具有圆形横截面形状的金属纳米结构。

    PHOTOCONDUCTOR AND IMAGE SENSOR USING THE SAME
    22.
    发明申请
    PHOTOCONDUCTOR AND IMAGE SENSOR USING THE SAME 有权
    光电子和图像传感器使用它

    公开(公告)号:US20160049536A1

    公开(公告)日:2016-02-18

    申请号:US14666057

    申请日:2015-03-23

    Abstract: A photoconductor includes a first semiconductor layer, a second semiconductor layer disposed on the first semiconductor layer, a first electrode connected to a first lateral side of the first semiconductor layer and the second semiconductor layer, and a second electrode connected to a second lateral side of the first semiconductor layer and the second semiconductor layer, where the first semiconductor layer and the second semiconductor layer form a type II junction or a quasi-type-II junction.

    Abstract translation: 光电导体包括第一半导体层,设置在第一半导体层上的第二半导体层,连接到第一半导体层和第二半导体层的第一横向侧的第一电极和连接到第一半导体层的第二侧面的第二电极 第一半导体层和第二半导体层,其中第一半导体层和第二半导体层形成II型结或准II型结。

    ELECTRONIC DEVICE FOR IDENTIFYING FORCE TOUCH AND METHOD FOR OPERATING SAME

    公开(公告)号:US20230359541A1

    公开(公告)日:2023-11-09

    申请号:US18224868

    申请日:2023-07-21

    CPC classification number: G06F11/3438 G06F11/3041

    Abstract: A method of identifying, in an electronic device, a force associated with a touch input of a user is provided. The method includes receiving at least one touch input from the user; obtaining first feature information for the at least one touch input; obtaining a plurality of force touch models configured to identify force touch; obtaining second feature information for at least one touch input included in training data used to train the plurality of force touch models; determining, from among the plurality of force touch models, a force touch model based on a similarity between the second feature information and the first feature information; and identifying, based on the determined force touch model, a force touch for the at least one touch input of the user.

    PERSONALIZED ELECTRONIC DEVICE INFERRING USER INPUT, AND METHOD FOR CONTROLLING SAME

    公开(公告)号:US20230359348A1

    公开(公告)日:2023-11-09

    申请号:US18221288

    申请日:2023-07-12

    CPC classification number: G06F3/04883 G06F3/0414

    Abstract: Provided is an electronic device configured to perform an operation corresponding to a user input by using an artificial intelligence model, and a method performed by the electronic device, of performing the operation. The method comprises obtaining touch data related to a touch input of a user, identifying a first training data set similar to the touch data from a plurality of pre-stored training data sets, training an artificial intelligence model based on the first training data set, identifying a type of a user input that is input to the electronic device, based on the trained artificial intelligence model, and performing an operation corresponding to the identified type of the user input.

    ELECTRONIC DEVICE AND CONTROL METHOD THEREOF

    公开(公告)号:US20230085127A1

    公开(公告)日:2023-03-16

    申请号:US17992659

    申请日:2022-11-22

    Abstract: An electronic device is provide, the electronic device including: a communication interface including at least one circuit; a memory including at least one instruction; and a processor. The processor is configured to: obtain a plurality of images, wherein the plurality of images include an one or more objects; obtain, by inputting the plurality of photographed images into a first neural network model for identifying objects: a feature value for each object of the one or more objects, a predicted class for each object of the one or more objects based on the respective obtained feature values, and a probability value for the predicted class for each of the one or more objects; identify an one or more learning images among the plurality of images based on the obtained probability values; identify one or more clusters of feature values by mapping the feature values of the one or more objects included in the one or more identified learning images to a vector space; obtain a learning data from the one or more identified learning images based on the obtained feature values; transmit the obtained learning data to an external device through the communication interface; receive an information on a second neural network model from the external device, and update the first neural network model based on the received information on the second neural network model.

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