METHOD FOR PROVIDING AND RECOGNIZING TRANSMISSION MODE IN DIGITAL BROADCASTING
    1.
    发明申请
    METHOD FOR PROVIDING AND RECOGNIZING TRANSMISSION MODE IN DIGITAL BROADCASTING 审中-公开
    在数字广播中提供和识别传输模式的方法

    公开(公告)号:US20150245006A1

    公开(公告)日:2015-08-27

    申请号:US14681443

    申请日:2015-04-08

    CPC classification number: H04N13/156 H04N21/4345 H04N21/816

    Abstract: The present invention relates to a method for selecting an appropriate mode when performing a new broadcast, such as a 3D stereo broadcast, a UHDTV broadcast, and a multi-view broadcast, among others, while maintaining compatibility with existing broadcasting channels in an MPEG-2-TS format for transmitting and receiving digital TV, and to a method for recognizing a descriptor. To this end, the present invention suggests providing the descriptor which is related to synthesizing left and right images using the type of stream, existence of the descriptor, and a frame-compatible mode flag.

    Abstract translation: 本发明涉及一种用于在执行诸如3D立体广播,UHDTV广播和多视点广播等新广播时选择适当模式的方法,同时保持与MPEG- 用于发送和接收数字TV的2-TS格式,以及用于识别描述符的方法。 为此,本发明提出使用流的类型,描述符的存在以及帧兼容模式标志来提供与合成左图像和右图像有关的描述符。

    METHOD FOR SEPARATING AUDIO SOURCES AND AUDIO SYSTEM USING THE SAME
    3.
    发明申请
    METHOD FOR SEPARATING AUDIO SOURCES AND AUDIO SYSTEM USING THE SAME 有权
    使用该方法分离音频源和音频系统

    公开(公告)号:US20150365766A1

    公开(公告)日:2015-12-17

    申请号:US14553188

    申请日:2014-11-25

    CPC classification number: G10L21/0272

    Abstract: A method for separating audio sources and an audio system using the same are provided. The method introduces the concept of a residual signal to separate a mixed audio signal into audio sources, and separates an audio signal corresponding to at least two of the audio sources as a residual signal and processes the audio signal separately. Therefore, audio separation performance can be improved. In addition, the method re-separates a separated residual signal and adds the separated residual signals to corresponding audio sources. Therefore, audio sources can be separated more safely.

    Abstract translation: 提供了一种用于分离音频源的方法和使用其的音频系统。 该方法引入残留信号的概念以将混合音频信号分离成音频源,并且将与至少两个音频源相对应的音频信号分离为残差信号并分别处理音频信号。 因此,可以提高音频分离性能。 此外,该方法重新分离分离的残差信号,并将分离的残留信号添加到相应的音频源。 因此,音频源可以更安全地分离。

    METHOD AND APPARATUS FOR GENERATING/CONVERTING DIGITAL HOLOGRAM
    4.
    发明申请
    METHOD AND APPARATUS FOR GENERATING/CONVERTING DIGITAL HOLOGRAM 审中-公开
    用于生成/转换数字HOLOGRAM的方法和装置

    公开(公告)号:US20150253730A1

    公开(公告)日:2015-09-10

    申请号:US14582354

    申请日:2014-12-24

    CPC classification number: G03H1/0808 G03H2210/452

    Abstract: A method and apparatus for generating/converting a digital hologram is provided. The method for generating the digital hologram includes: clustering points of a 3D object to a plurality of clusters according to a distance to a screen; generating diffraction patterns in a unit of a cluster; and generating a fringe pattern by overlapping the diffraction patterns with one another. Accordingly, calculation complexity can be reduced and thus it is possible to generate a digital hologram at high speed. Since a range/size of a cluster which has a trade-off relationship with an image quality of a digital hologram is adjustable, it is possible to generate a customized flexible digital hologram.

    Abstract translation: 提供了一种用于产生/转换数字全息图的方法和装置。 用于生成数字全息图的方法包括:根据到屏幕的距离将3D对象的聚类点与多个聚类; 以簇为单位产生衍射图; 以及通过将衍射图案彼此重叠而产生条纹图案。 因此,可以减少计算复杂度,从而可以高速生成数字全息图。 由于与数字全息图的图像质量具有权衡关系的聚类的范围/尺寸是可调节的,所以可以生成定制的柔性数字全息图。

    METHOD AND APPARATUS FOR ENCODING/DECODING DEEP LEARNING NETWORK

    公开(公告)号:US20230010859A1

    公开(公告)日:2023-01-12

    申请号:US17784862

    申请日:2020-11-30

    Abstract: Disclosed herein are a method and apparatus for encoding/decoding a deep learning network. According to an embodiment, the method for decoding a deep learning network may include decoding network header information regarding the deep learning network; decoding layer header information regarding a plurality of layers in the deep learning network; decoding layer data information regarding specific information of the plurality of layers; and obtaining the deep learning network and a plurality of layers in the deep learning network, and the layer header information includes layer distinction information associated with distinguishing the plurality of layers.

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