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| Machine Layout Problem in Direcect-Input-Output Manufacturing System 황학, 산업공학(IE INTERFACES), v.9, no.2, pp.203 - 218, 1996-01 |
| Machine learning (ML)-based lithography optimizations Shin, Youngsoo; Shim, Seongbo; Choi, Suhyeong, IEEE Asia Pacific Conference on Circuits and Systems, IEEE, 2016-10-25 |
| Machine learning (ML)-guided OPC using basis functions of polar Fourier transform Shim, Seongbo; Choi, Su Hyeong; Shin, Young Soo, SPIE Advanced Lithography, SPIE, 2016-02-24 |
| Machine Learning Acceleration Esmaeilzadeh, Hadi; Park, Jongse, IEEE MICRO, v.39, no.5, pp.6 - 7, 2019-09 |
| Machine learning acceleration method with multidimensional data embedding and coded distributed computing for internet of things = 다차원 데이터 임베딩과 코드화된 분산 컴퓨팅을 통한 사물인터넷 환경에서의 기계학습 가속화 방법link Kim, Nakyoung, 한국과학기술원, 2021 |
| Machine learning algorithms for sparse supervision = 저지도 상황에서의 기계학습 알고리즘 연구link Seo, Jun; Moon, Jaekyun; et al, 한국과학기술원, 2022 |
| Machine Learning and Autonomous Systems in the Military Realm: An Engineer’s Point of View Lee, Soo-Young, 3rd SIPRI Workshop on Mapping the Impact of Machine Learning and Autonomy on Strategic Stability and Nuclear Risk, STOCKHOLM INTERNATIONAL PEACE RESEARCH INSTITUTE, 2019-02-25 |
| Machine learning application to seismic site classification prediction model using Horizontal-to-Vertical Spectral Ratio (HVSR) of strong-ground motions Phi, Francis G.; Cho, Bumsu; Kim, Jungeun; Cho, Hyungik; Choo, Yun Wook; Kim, Dookie; Kim, Inhi, Geomechanics and Engineering, v.37, no.6, pp.539 - 554, 2024-06 |
| Machine learning applications in genome-scale metabolic modeling Kim, Yeji; Kim, Gi Bae; Lee, Sang Yup, Current Opinion in Systems Biology, v.25, pp.42 - 49, 2021-03 |
| Machine learning applications in systems metabolic engineering Kim, Gi Bae; Kim, Won Jun; Kim, Hyun Uk; Lee, Sang Yup, CURRENT OPINION IN BIOTECHNOLOGY, v.64, pp.1 - 9, 2020-08 |
| Machine learning approach for anonymizing electronic medical records = 전자의무기록의 기계학습 기반 익명화 기법link Shin, Moon-Shik; 신문식; et al, 한국과학기술원, 2012 |
| Machine Learning Approach for Inverse Scattering Problem = 기계학습을 이용한 역산란 문제 연구link Yoo, Jaejun; Ye, Jong Chul; et al, 한국과학기술원, 2018 |
| Machine Learning Approach to Yield Management in Semiconductor Manufacturing: Continuous Class Learning Approaches Park, Sang Chan, Int'l Conf. on Production Research, pp.1219 - 1222, 1999 |
| Machine learning approaches for materials discovery: Predictive and generative models Jung, Yousung, Telluride Workshop Machine Learning and Informatics for Chemistry and Materials, Telluride Science Research Center, 2018-10-01 |
| Machine learning approaches to the configuration energies and chemisorption models in solids Jung, Yousung, Machine Learning for Energy Materials Discovery, MIT, 2017-05-30 |
| Machine learning approaches to the configuration energies and chemisorption models in solids Jung, Yousung, IPAM(Institute for Pure & Applied mathematics)Workshop I: Machine Learning Meets Many-Particle Problems, ipam, 2016-09-26 |
| Machine learning approaches to the configuration energies and chemisorption models in solids Jung, Yousung, 대한화학회 제 118회 총회 및 학술발표회, 대한화학회, 2016-10-13 |
| Machine Learning Approaches to the Configuration Energies and Chemisorption Models in Solids Jung, Yousung, 2017 Symposium for the Promotion of Applied Research Collaboration in Asia, Asia Pacific Society for Materials Science (APSMR), 2017-02-26 |
| Machine learning assisted characterization of atherosclerotic plaque components via multispectral fluorescence lifetime imaging microscopy Han, Jeongmoo; Kim, Sunwon; Kim, Hyun Jung; Nam, Hyeong Soo; Kim, Jin Won; Yoo, Hongki, SPIE Photonics West 2023, SPIE, 2023-01-29 |
| Machine learning assisted non-destructive beam profile monitoring Omarov, Zhanibek; Haciomeroglu, Selcuk, NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, v.1026, 2022-03 |
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