Search Results - "Kim, Youngdong"

Joint Negative and Positive Learning for Noisy Labels by Kim, Youngdong, Yun, Juseung, Shon, Hyounguk, Kim, Junmo

“…Training of Convolutional Neural Networks (CNNs) with data with noisy labels is known to be a challenge. Based on the fact that directly providing the label to…”
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Fairness-based Bidding Model for Renewable Portfolio Standard Policy in South Korea Standard Policy in South Korea by Kim, Youngdong, Kim, Kyungdoh, Seok, Hyesung

“…The share of renewable energy has already exceeded that of nuclear power in the United Kindom, Germany (by 30%), and Japan (10%), whereas the supply of…”
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NLNL: Negative Learning for Noisy Labels by Kim, Youngdong, Yim, Junho, Yun, Juseung, Kim, Junmo

“…Convolutional Neural Networks (CNNs) provide excellent performance when used for image classification. The classical method of training CNNs is by labeling…”
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A model for predicting the friction of micro patterns fabricated by precision machining by Kim, Youngdong, Yoon, Hae-Sung

“…This study aims to construct a model facilitating the design of patterns with desirable friction characteristics by investigating the effects of pattern…”
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Excellent Endurance (> 10 13 ) of Charge Trap Memory Based on H x WO 3 Charge Trap Layer With Shallow Trap Level Using Hydrogen Spillover by Han, Geonhui, Kim, Jaeseon, Kim, Youngdong, Seo, Jongseon, Lee, Donghwa, Hwang, Hyunsang

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Excellent Endurance (> 1013) of Charge Trap Memory Based on HxWO3 Charge Trap Layer With Shallow Trap Level Using Hydrogen Spillover by Han, Geonhui, Kim, Jaeseon, Kim, Youngdong, Seo, Jongseon, Lee, Donghwa, Hwang, Hyunsang

“…In this study, we present an IGZO-based volatile charge trap memory, employing a hydrogenated WO 3 (H x WO<inline-formula> <tex-math…”
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1013) of Charge Trap Memory Based on HxWO3 Charge Trap Layer With Shallow Trap Level Using Hydrogen Spillover by Han, Geonhui, Kim, Jaeseon, Kim, Youngdong, Seo, Jongseon, Lee, Donghwa, Hwang, Hyunsang

“…10%) was realized in the CTL owing to low activation energy with hydrogen spillover. In addition, both experimental results and Density Functional Theory…”
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The synthetic chemoattractant peptide WKYMVm induces superoxide production by human eosinophils via the phosphoinositide 3-kinase-mediated activation of ERK1/2 by Shin, Myeong Heon, Lee, Young-Ah, Bae, Yoe-Sik, Kita, Hirohito, Kim, Youngdong, Ryu, Sung Ho

“…Eosinophils play a key role in allergic inflammation and parasitic infections. The synthetic peptide, Trp-Lys-Tyr-Met-Val-D-Met (WKYMVm), has been previously…”
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BiasAdv: Bias-Adversarial Augmentation for Model Debiasing by Lim, Jongin, Kim, Youngdong, Kim, Byungjai, Ahn, Chanho, Shin, Jinwoo, Yang, Eunho, Han, Seungju

“…Neural networks are often prone to bias toward spurious correlations inherent in a dataset, thus failing to generalize unbiased test criteria. A key challenge…”
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Highly Scalable Vertical Bypass RRAM (VB-RRAM) for 3D V -NAND Memory by Han, Geonhui, Kim, Youngdong, Kim, Jaeseon, Kim, Dongmin, Seo, Yoori, Lee, Chuljun, Choi, Jinmyung, Lee, Jinwoo, Ahn, Dongho, Oh, Sechung, Lee, Donghwa, Hwang, Hyunsang

“…We firstly demonstrate highly scalable interface type RRAM based 3D V-NAND memory with WOx resistivity switching (RS) layer and IGZO selector transistor (Tr)…”
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The origin and relationships of the pepino, Solanum muricatum (Solanaceae): DNA restriction fragment evidence by Anderson, G.J. (University of Connecticut, Storrs, CT.), Jansen, R.K, Kim, Y

“…The pepino (or pepino dulce: Solanum muricatum) is a domesticate of interest because of its close relationship to tomatoes and potatoes, because it is enjoying…”
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Joint Negative and Positive Learning for Noisy Labels by Kim, Youngdong, Yun, Juseung, Shon, Hyounguk, Kim, Junmo

“…Training of Convolutional Neural Networks (CNNs) with data with noisy labels is known to be a challenge. Based on the fact that directly providing the label to…”
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NLNL: Negative Learning for Noisy Labels by Kim, Youngdong, Yim, Junho, Yun, Juseung, Kim, Junmo

“…Convolutional Neural Networks (CNNs) provide excellent performance when used for image classification. The classical method of training CNNs is by labeling…”
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Learning from Imbalanced and Hierarchically Dual-Labeled Data by Yun, Juseung, Kim, Youngdong, Yim, Junho, Cho, Hansang, Kim, Junmo

“…The success of deep neural networks depends strongly on the availability of balanced and well-refined datasets, but in a real industry or practical cases, it…”
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Molecular phylogenetic studies of the Berberidaceae by Kim, Youngdong

“…In spite of extensive studies using chromosome number, floral anatomy, pollen morphology, and serology, substantial disagreement still remains in the…”
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Refine pedestrian detections by referring to features in different ways by Lee, Jaemyung, Lee, Sihaeng, Kim, Youngdong, Lee, Janghyeon, Kim, Junmo

“…The performance of object detection has been improved as the success of deep architectures. The main algorithm predominantly used for general detection is…”
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Molecular phylogenetic studies of the Berberidaceae by Kim, Youngdong

“…In spite of extensive studies using chromosome number, floral anatomy, pollen morphology, and serology, substantial disagreement still remains in the…”
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Leukemia-specific siRNA delivery by immunonanoplexes consisting of anti-JL1 minibody conjugated to oligo-9 Arg-peptides by Lee, Yeon Kyung, Kim, Keun Sik, Kim, Jung Seok, Baek, Jin Ee, Park, Sang Il, Jeong, Hwa Yeon, Yoon, Sang Soon, Jung, Kyeong Cheon, Song, Hyung Geun, Park, Yong Serk

“…Targeted mRNA degradation by short interfering RNAs (siRNAs) offers a great potential to treat cancers. siRNA therapeutics for leukemias are, however, hindered…”
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A design of asymmetric double t-type microstrip dipole antennas by GeumGon Oh, YoungDong Kim

“…A wide band asymmetric double t-type microstrip dipole antenna for integrated circuits such as MMIC is designed and fabricated. A new configuration for a wide…”
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Definitive Nomenclature of GES/IBC-Type Extended-Spectrum β-Lactamases by Weldhagen, Gerhard F. (University of Pretoria, Pretoria, South Africa), Kim, B.H. (Youngdong University, Youngdong, Republic of Korea), Cho, C.H. (Youngdong University, Youngdong, Republic of Korea), Lee, S.H. (Youngdong University, Youngdong, Republic of Korea), E-mail: sangheelee@mju.ac.kr

“…Because there are no unified nomenclature systems for either GES-type or IBC-type extended-spectrum β-lactamases (ESBLs), we propose a unified and definitive…”
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