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公开(公告)号:US20240314390A1
公开(公告)日:2024-09-19
申请号:US18576912
申请日:2022-02-14
Applicant: KOREA ELECTRONICS TECHNOLOGY INSTITUTE
Inventor: Sung Jei KIM , Jin Woo JEONG , Seung Ho LEE , Hyeon Cheol MOON
IPC: H04N21/4402 , H04N19/70 , H04N21/234 , H04N21/25
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.
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公开(公告)号:US20230010859A1
公开(公告)日:2023-01-12
申请号:US17784862
申请日:2020-11-30
Applicant: Korea Electronics Technology Institute
Inventor: Byeong Ho CHOI , Sang Seol LEE , Sung Joon JANG , Sung Jei KIM
IPC: G06N3/08
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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公开(公告)号:US20230008124A1
公开(公告)日:2023-01-12
申请号:US17784856
申请日:2020-12-11
Applicant: Korea Electronics Technology Institute , INDUSTRY-UNIVERSITY COOPERATION FOUNDATION KOAEA AEROSPACE UNIVERSITY
Inventor: Byeong Ho CHOI , Sang Seol LEE , Sung Joon JANG , Sung Jei KIM , Jae Gon KIM , Hyeon Cheol MOON
IPC: G06N3/04
Abstract: Disclosed herein are a method and apparatus for encoding/decoding a deep neural network. According to the present disclosure, the method for decoding a deep neural network may include: in a plurality of layers of the deep neural network, entropy decoding quantization information for a current layer; performing dequantization on the current layer; and obtaining a plurality of layers of the deep neural network. At least one of global quantization and local quantization is performed on the current layer.
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