1 code implementation • 20 Nov 2022 • Junho Cho, Kyuewang Lee, Jin Young Choi
For the discriminative representation of a font from others, we propose a paired-glyph matching-based font representation learning model that attracts the representations of glyphs in the same font to one another, but pushes away those of other fonts.
no code implementations • 25 Feb 2022 • Junho Cho, Xi Chen, Greg Raybon, Son Thai Le
We show that digital subcarrier multiplexing (DSM) systems require much greater complexity for Nyquist pulse shaping than single-carrier (SC) systems, and it is a misconception that both systems use the same bandwidth when using the same pulse shaping.
no code implementations • 7 Dec 2021 • Junho Cho, Robert Tkach
Knowing only two high-order statistical moments of modulation symbols, often represented by the fourth moment called "kurtosis", the overestimation of nonlinear interference (NLI) in a Gaussian noise (GN) model due to Gaussian signaling assumption can be corrected through an enhanced GN (EGN) model.
no code implementations • 12 Sep 2021 • Son Thai Le, Vahid Aref, Junho Cho
One potential approach for solving this problem is to leverage the concept of single-ended coherent receiver (SER) where single-ended PDs are used instead of the balanced PDs.
1 code implementation • CVPR 2021 • Jiwoong Park, Junho Cho, Hyung Jin Chang, Jin Young Choi
Most of the existing literature regarding hyperbolic embedding concentrate upon supervised learning, whereas the use of unsupervised hyperbolic embedding is less well explored.
no code implementations • 28 Feb 2021 • Hanzi Huang, Yetian Huang, Haoshuo Chen, Qianwu Zhang, Jian Chen, Nicolas K. Fontaine, Mikael Mazur, Roland Ryf, Junho Cho, Yingxiong Song
We propose a digital interference mitigation scheme to reduce the impact of mode coupling in space division multiplexing self-homodyne coherent detection and experimentally verify its effectiveness in 240-Gbps mode-multiplexed transmission over 3-mode multimode fiber.
no code implementations • 9 Feb 2021 • Di Che, Junho Cho, Xi Chen
Probabilistic constellation shaping (PCS) has been widely applied to amplified coherent optical transmissions owing to its shaping gain over the uniform signaling and fine-grained rate adaptation to the underlying fiber channel condition.
no code implementations • 9 Dec 2020 • Junho Cho, Xi Chen, Greg Raybon, Di Che, Ellsworth Burrows, Robert Tkach
By tailoring probabilistic constellation shaping (PCS) for nonlinearity tolerance, we experimentally demonstrate up to 1. 1 dB increase in signal-to-noise ratio (SNR) and 6. 4% increase in total net data rate (NDR) compared to linear-channel-optimized PCS on a 2824-km dispersion-managed wavelength-division multiplexed (WDM) optical fiber link.
no code implementations • 23 Sep 2020 • Xi Chen, Ken Tanizawa, Peter Winzer, Po Dong, Junho Cho, Fumio Futami, Kentaro Kato, Argishti Melikyan, Kw Kim
We demonstrate a 4, 294, 967, 296-ary quadrature amplitude modulation (QAM) based Y-00 quantum stream cipher system carrying 160-Gb/s 16-QAM signal transmitted over 320-km SSMF.
no code implementations • 2 Oct 2019 • Junho Cho, Sethumadhavan Chandrasekhar, Erixhen Sula, Samuel Olsson, Ellsworth Burrows, Greg Raybon, Roland Ryf, Nicolas Fontaine, Jean-Christophe Antona, Steve Grubb, Peter Winzer, Andrew Chraplyvy
We experimentally achieve a 19% capacity gain per Watt of electrical supply power in a 12-span link by eliminating gain flattening filters and optimizing launch powers using machine learning by deep neural networks in a massively parallel fiber context.
1 code implementation • The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2017 • Junho Cho, Sangdoo Yun, Kyoung Mu Lee, Jin Young Choi
PaletteNet is then designed to change the color concept of a source image so that the palette of the output image is close to the target palette.