Zobrazeno 1 - 10
of 87
pro vyhledávání: '"Seoung Jun Oh"'
Autor:
Minhun Lee, Hansol Choi, Jihoon Kim, Jihoon Do, Hyoungjin Kwon, Se Yoon Jeong, Donggyu Sim, Seoung-Jun Oh
Publikováno v:
IEEE Access, Vol 11, Pp 26308-26319 (2023)
This paper presents a method to effectively compress the intermediate layer feature map of a convolutional neural network for the potential structures of Video Coding for Machines, which is an emerging technology for future machine consumption applic
Externí odkaz:
https://doaj.org/article/6df67ae77e6245adb4f69ed7b4aed9b8
Publikováno v:
Electronics Letters, Vol 59, Iss 19, Pp n/a-n/a (2023)
Abstract Geometric partitioning mode (GPM) was newly adopted in Versatile Video Coding (VVC) to increase the partitioning precision of the arbitrary boundaries of actual objects. Note that the blending process of the GPM is not suitable for screen co
Externí odkaz:
https://doaj.org/article/9e74af37b50a416096330ca31bc466d0
Publikováno v:
Remote Sensing, Vol 13, Iss 8, p 1482 (2021)
In this paper, a convolutional neural network-based registration framework is proposed for remote sensing to improve the registration accuracy between two remote-sensed images acquired from different times and viewpoints. The proposed framework consi
Externí odkaz:
https://doaj.org/article/333eee66f26c4a6a8a1c74bba613d88e
Publikováno v:
International Workshop on Advanced Imaging Technology (IWAIT) 2023.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::11c94b311f46c4a3392856a87e35cfea
https://doi.org/10.1117/12.2666465
https://doi.org/10.1117/12.2666465
Publikováno v:
2022 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d5160bad6c0cc61a8a9dbc099fa70631
https://doi.org/10.1109/icce-asia57006.2022.9954773
https://doi.org/10.1109/icce-asia57006.2022.9954773
Autor:
Seoung-Jun Oh, Woo-Ju Lee
Publikováno v:
ICOIN
We propose a deep learning-based framework for remote sensing image registration using equivariance features. Unlike conventional methods, the networks in the framework are trained on not invariance features but equivariance features since keeping in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6987e37fc976b417076f4fc776e58140
https://doi.org/10.1109/icoin50884.2021.9333861
https://doi.org/10.1109/icoin50884.2021.9333861
Publikováno v:
Remote Sensing, Vol 13, Iss 1482, p 1482 (2021)
Remote Sensing; Volume 13; Issue 8; Pages: 1482
Remote Sensing; Volume 13; Issue 8; Pages: 1482
In this paper, a convolutional neural network-based registration framework is proposed for remote sensing to improve the registration accuracy between two remote-sensed images acquired from different times and viewpoints. The proposed framework consi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::beab4353e6049d4478eef14da6abc95b
https://doi.org/10.3390/rs13081482
https://doi.org/10.3390/rs13081482
Publikováno v:
The Journal of Korean Institute of Communications and Information Sciences. 41:1120-1131
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e5f8a2d8fa130d02c55af49bb7223acf
https://doi.org/10.7840/kics.2016.41.9.1120
https://doi.org/10.7840/kics.2016.41.9.1120
Publikováno v:
Journal of Real-Time Image Processing. 12:549-562
The recent video compression standard, HEVC (high efficiency video coding), will most likely be used in various applications in the near future. However, the encoding process is far too slow for real-time applications. At the same time, computing cap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0b3e60cc35a730143fe002b5d77e096
https://doi.org/10.1007/s11554-015-0522-6
https://doi.org/10.1007/s11554-015-0522-6
Publikováno v:
Journal of Broadcast Engineering. 20:533-544
"./0123 4256789:; 4 ?@A. BCD789:; PBQ>RSN"46TUV (Error Concealment : EC) WXYZ OI A. OIB6WXYZ"46High Efficiency Video Coding (HEVC) E "4[\]#^=(_ `abQ 1 (Adaptive Prediction Unit-based Motion Vector Extrapolation : APMVE) c\]#^=(_ (Boundary Matching :
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64293aa8f58652d8aa260f24a83e2cfb
https://doi.org/10.5909/jbe.2015.20.4.533
https://doi.org/10.5909/jbe.2015.20.4.533