Electronic apparatus and controlling method thereof

    公开(公告)号:US11350171B2

    公开(公告)日:2022-05-31

    申请号:US16887641

    申请日:2020-05-29

    Abstract: An electronic apparatus is provided. The electronic apparatus includes: a memory configured to store volume histories for a plurality of content sources; and a processor configured to, based on a content source for providing a content being changed from a first content source to a second content source, among the plurality of content sources, identify a volume level corresponding to the second content source based on a volume history of the first content source and a volume history of the second content source among the stored volume histories, and change a currently-set volume level to the identified volume level, and update the volume history of the second content source based on the changed volume level.

    Semiconductor device and method of fabricating the same

    公开(公告)号:US11314919B2

    公开(公告)日:2022-04-26

    申请号:US17022233

    申请日:2020-09-16

    Abstract: Disclosed are a semiconductor device and a method of fabricating the same. The semiconductor device includes an area-oriented region and a performance-oriented region, standard cells disposed on each of the area-oriented region and the performance-oriented region, and a routing metal layer on the standard cells. The routing metal layer includes first routing lines on the area-oriented region and second routing lines on the performance-oriented region. The smallest line width of the first routing lines is a first width, the smallest line width of the second routing lines is a second width greater than the first width, a pitch between the first routing lines is a first pitch, and a pitch between the second routing lines is a second pitch greater than the first pitch.

    Semiconductor device and method of fabricating the same

    公开(公告)号:US11995391B2

    公开(公告)日:2024-05-28

    申请号:US17702879

    申请日:2022-03-24

    CPC classification number: G06F30/3953 G03F1/36 G06F30/392 G06F30/398

    Abstract: Disclosed are a semiconductor device and a method of fabricating the same. The semiconductor device includes an area-oriented region and a performance-oriented region, standard cells disposed on each of the area-oriented region and the performance-oriented region, and a routing metal layer on the standard cells. The routing metal layer includes first routing lines on the area-oriented region and second routing lines on the performance-oriented region. The smallest line width of the first routing lines is a first width, the smallest line width of the second routing lines is a second width greater than the first width, a pitch between the first routing lines is a first pitch, and a pitch between the second routing lines is a second pitch greater than the first pitch.

    ELECTRONIC DEVICE AND METHOD OF SETTING OPERATION MODE THEREOF

    公开(公告)号:US20230281020A1

    公开(公告)日:2023-09-07

    申请号:US18120163

    申请日:2023-03-10

    CPC classification number: G06F9/44505 G06F3/147

    Abstract: A method including identifying the operation mode of the electronic device as a first operation mode, sensing a change of setting corresponding to the first operation mode, determining whether to update setting information about the setting, based on at least one of a changing pattern or a change history of a user, and when the operation mode is identified later as the first operation mode, providing the user with the first operation mode with the plurality of updated settings including the setting information about the updated setting is provided.

    Non-transitory computer-readable medium and method for monitoring a semiconductor fabrication process

    公开(公告)号:US10949949B2

    公开(公告)日:2021-03-16

    申请号:US16402375

    申请日:2019-05-03

    Abstract: A non-transitory computer-readable medium for monitoring a semiconductor fabrication process includes an image conversion model having an artificial neural network. The image conversion model, when executed, causes the processor to receive a first image and a second image of a semiconductor wafer. The artificial neural network is trained by inputting a dataset representing the first image and the second image, generating a conversion image of the semiconductor wafer and calibrating weights and biases of the artificial neural network to match the conversion image to the second image. A third image of the semiconductor wafer is generated based on the calibrated weights and biases of the artificial neural network. The image conversion model with the trained artificial neural network may be transmitted to another device for image conversion of low resolution images.

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