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Institution

Samsung

CompanySeoul, South Korea
About: Samsung is a company organization based out in Seoul, South Korea. It is known for research contribution in the topics: Layer (electronics) & Signal. The organization has 134067 authors who have published 163691 publications receiving 2057505 citations. The organization is also known as: Samsung Group & Samsung chaebol.


Papers
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Journal ArticleDOI
TL;DR: An integrated organic functional material design process that incorporates theoretical insight, quantum chemistry, cheminformatics, machine learning, industrial expertise, organic synthesis, molecular characterization, device fabrication and optoelectronic testing is reported.
Abstract: A high-throughput virtual screening approach is used to select molecules with efficient, thermally activated delayed fluorescence. The good performance of several selected emitters in organic LED applications has also been confirmed experimentally.

711 citations

Journal ArticleDOI
Kinam Kim1, Jae-Young Choi1, Taek Kim1, Seong-Ho Cho1, Hyun-Jong Chung1 
17 Nov 2011-Nature
TL;DR: Graphene is unlikely to replace silicon completely, however, because of the poor on/off current ratio resulting from its zero bandgap, but it could be used to improve silicon-based devices, in particular in high-speed electronics and optical modulators.
Abstract: As silicon-based electronics approach the limit of improvements to performance and capacity through dimensional scaling, attention in the semiconductor field has turned to graphene, a single layer of carbon atoms arranged in a honeycomb lattice. Its high mobility of charge carriers (electrons and holes) could lead to its use in the next generation of high-performance devices. Graphene is unlikely to replace silicon completely, however, because of the poor on/off current ratio resulting from its zero bandgap. But it could be used to improve silicon-based devices, in particular in high-speed electronics and optical modulators.

707 citations

Patent
05 May 2014
TL;DR: In this paper, an organic light-emitting display (OLED) was proposed to display an image with high contrast and/or impact resistance, where a sealing member was placed on the organic light emitting device and a semitransparent film on a surface of the sealing member facing away from the OLED device.
Abstract: An organic light emitting display apparatus that has high (or improved) contrast and/or impact resistance. The organic light emitting display apparatus includes: a substrate; an organic light emitting device on the substrate to display an image; a sealing member on the organic light emitting device; a semitransparent film on a surface of the sealing member facing away from the organic light emitting device to transmit a portion of external light and to reflect another portion of the external light; a passivation film on the semitransparent film to protect the semitransparent film; and a transmissive black layer between the sealing member and the organic light emitting device to increase contrast, wherein the semitransparent film has a refractive index greater than that of the passivation film.

699 citations

Proceedings Article
01 Jan 2016
TL;DR: In this article, a simple and effective scheme to compress the entire CNN, which is called one-shot whole network compression, is presented, which consists of three steps: rank selection with variational Bayesian matrix factorization, Tucker decomposition on kernel tensor, and fine-tuning to recover accumulated loss of accuracy.
Abstract: Although the latest high-end smartphone has powerful CPU and GPU, running deeper convolutional neural networks (CNNs) for complex tasks such as ImageNet classification on mobile devices is challenging. To deploy deep CNNs on mobile devices, we present a simple and effective scheme to compress the entire CNN, which we call one-shot whole network compression. The proposed scheme consists of three steps: (1) rank selection with variational Bayesian matrix factorization, (2) Tucker decomposition on kernel tensor, and (3) fine-tuning to recover accumulated loss of accuracy, and each step can be easily implemented using publicly available tools. We demonstrate the effectiveness of the proposed scheme by testing the performance of various compressed CNNs (AlexNet, VGGS, GoogLeNet, and VGG-16) on the smartphone. Significant reductions in model size, runtime, and energy consumption are obtained, at the cost of small loss in accuracy. In addition, we address the important implementation level issue on 1?1 convolution, which is a key operation of inception module of GoogLeNet as well as CNNs compressed by our proposed scheme.

691 citations

Journal ArticleDOI
TL;DR: XP showed significant noninferiority for PFS versus FP in the first-line treatment of AGC and can be considered an effective alternative to FP.

688 citations


Authors

Showing all 134111 results

NameH-indexPapersCitations
Yi Cui2201015199725
Hyun-Chul Kim1764076183227
Hannes Jung1592069125069
Yongsun Kim1562588145619
Yu Huang136149289209
Robert W. Heath128104973171
Shuicheng Yan12381066192
Shi Xue Dou122202874031
Young Hee Lee122116861107
Alan L. Yuille11980478054
Yang-Kook Sun11778158912
Sang Yup Lee117100553257
Guoxiu Wang11765446145
Richard G. Baraniuk10777057550
Jef D. Boeke10645652598
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20239
202289
20213,059
20205,735
20195,994
20185,885