ELECTRONIC DEVICE, SYSTEM, AND METHOD FOR INTELLIGENT HORIZONTAL-VERTICAL IMAGE TRANSFORM

    公开(公告)号:US20240314390A1

    公开(公告)日:2024-09-19

    申请号:US18576912

    申请日:2022-02-14

    CPC classification number: H04N21/440272 H04N19/70 H04N21/23418 H04N21/251

    Abstract: Proposed is an electronic device, a system, and a method for intelligent horizontal-vertical image conversion. The device may transmit a bitstream containing information on an image having a first image ratio that is longer horizontally than vertically to a terminal to enlarge and reproduce the image when the terminal has a screen ratio state that is longer vertically than horizontally. The device may include an analysis controller for analyzing contents of a corresponding frame image to calculate a corresponding reproduction area. The device may also include a selection controller for separating the image into a plurality of subunits, and selecting an optimal artificial intelligence (AI) model applied for each subunit according to the contents of the image within the corresponding subunit from among a plurality of previously trained AI models. The device may further include a generation controller for generating the bitstream, the reproduction area, and the optimal AI model.

    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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