METHOD AND APPARATUS WITH SENSOR CALIBRATION

    公开(公告)号:US20220414933A1

    公开(公告)日:2022-12-29

    申请号:US17575092

    申请日:2022-01-13

    Abstract: A processor-implemented method with sensor calibration includes: estimating a portion of a rotation parameter for a target sensor among a plurality of sensors based on a capture of a reference object; estimating another portion of the rotation parameter for the target sensor based on an intrinsic parameter of the target sensor and a focus of expansion (FOE) determined based on sensing data collected with consecutive frames by the target sensor while the electronic device rectilinearly moves based on one axis; and performing calibration by determining a first extrinsic parameter for the target sensor based on the portion and the other portion of the rotation parameter.

    METHOD AND APPARATUS WITH ADAPTIVE OBJECT TRACKING

    公开(公告)号:US20220138493A1

    公开(公告)日:2022-05-05

    申请号:US17246803

    申请日:2021-05-03

    Abstract: Disclosed is a method and apparatus for adaptive tracking of a target object. The method includes method of tracking an object, the method including estimating a dynamic characteristic of an object in an input image based on frames of the input image, determining a size of a crop region for a current frame of the input image based on the dynamic characteristic of the object, generating a cropped image by cropping the current frame based on the size of the crop region, and generating a result of tracking the object for the current frame using the cropped image.

    METHOD AND APPARATUS WITH NEURAL NETWORK OPERATION PROCESSING

    公开(公告)号:US20220019895A1

    公开(公告)日:2022-01-20

    申请号:US17124791

    申请日:2020-12-17

    Abstract: A processor-implemented neural network method includes: obtaining a first weight kernel of a weight model and pruning information of the first weight kernel; determining, based on the pruning information, a processing range of an input feature map for each weight element vector of the first weight kernel; performing a convolution operation between the input feature map and the first weight kernel based on the determined processing range; and generating an output feature map of a neural network layer based on an operation result of the convolution operation.

    ORGANIC-INORGANIC COMPOSITE FILMS AND METHODS OF MANUFACTURING THE SAME
    18.
    发明申请
    ORGANIC-INORGANIC COMPOSITE FILMS AND METHODS OF MANUFACTURING THE SAME 有权
    有机无机复合膜及其制造方法

    公开(公告)号:US20160103233A1

    公开(公告)日:2016-04-14

    申请号:US14738530

    申请日:2015-06-12

    CPC classification number: G01T1/244 G01T1/24 H01B1/02 H01L27/14676

    Abstract: A method of manufacturing an organic-inorganic composite thin film may include: forming a thin film from a paste that includes an inorganic powder and an organic compound binder by using a screen printing process; and/or performing a pressing process and a heating process with respect to the thin film. The heating process may be performed at a glass transition temperature of the organic compound binder or in a temperature range higher than the glass transition temperature of the organic compound binder. An X-ray detector configured to detect X-rays irradiated from an outside of the X-ray detector may include: a photoconductive material layer in which electron-hole pairs are formed due to absorption of the X-rays. The photoconductive material layer may be formed of an organic-inorganic composite thin film that includes an inorganic powder and an organic compound binder.

    Abstract translation: 制造有机 - 无机复合薄膜的方法可以包括:通过使用丝网印刷方法从包含无机粉末和有机化合物粘合剂的糊状物形成薄膜; 和/或对薄膜进行加压处理和加热处理。 加热过程可以在有机化合物粘合剂的玻璃化转变温度下或在高于有机化合物粘合剂的玻璃化转变温度的温度范围内进行。 用于检测从X射线检测器外部照射的X射线的X射线检测器可以包括:由于吸收X射线而形成电子 - 空穴对的感光材料层。 光导材料层可以由包含无机粉末和有机化合物粘合剂的有机 - 无机复合薄膜形成。

    METHODS AND SYSTEMS FOR FACILITATING MULTIPLE COMMUNICATION TECHNOLOGIES USING A SINGLE CHIP RADIO

    公开(公告)号:US20240256265A1

    公开(公告)日:2024-08-01

    申请号:US18636567

    申请日:2024-04-16

    CPC classification number: G06F8/654

    Abstract: Methods and systems for dynamically updating firmware of a single-protocol based one-chip radio device present in an Internet of things (IoT) environment with multiple technologies using an intelligent firmware update based on size of the flash memory, the one or more hardware resources available at the controller level, and a current IoT context associated with the IoT environment are provided. The method includes receiving a firmware update package, determining a size of flash memory and one or more hardware resources at a controller level of the single-protocol, based on receiving the firmware update package, correlating the received firmware update package with the size of the flash memory, dynamically selecting one or more firmware resources from the received firmware package for updating firmware of the single-protocol based one-chip radio device based on the correlation, and updating firmware of the single-protocol based one-chip radio device using the one or more firmware resources.

    METHOD AND APPARATUS WITH ATTENTION-BASED OBJECT ANALYSIS

    公开(公告)号:US20240153130A1

    公开(公告)日:2024-05-09

    申请号:US18342892

    申请日:2023-06-28

    CPC classification number: G06T7/73 G06T7/50 G06V10/25 G06V10/764 G06V10/771

    Abstract: An apparatus includes one or more processors configured to generate a plurality of feature maps having respective different resolutions based on an input image; and update, for each of the plurality of transformer layers, respective position estimation information comprising first position information of a respective bounding box corresponding to one object query and second position information of respective key points corresponding to the one object query, wherein each of the plurality of transformer layers includes a self-attention model configured to generate respective intermediate data by performing self-attention on respective content information on a feature of the input image; and a cross-attention model configured to generate respective output data by performing cross-attention on respective one or more feature maps among the plurality of feature maps and the respective generated intermediate data.

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