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| Deep learning forecasting using time-varying parameters of the SIRD model for Covid-19 Bousquet, Arthur; Conrad, William H.; Sadat, Said Omer; Vardanyan, Nelli; Hong, Youngjoon, SCIENTIFIC REPORTS, v.12, no.1, 2022-02 |
Deep learning framework for material design space exploration using active transfer learning and data augmentation Kim, Yongtae; Kim, Youngsoo; Yang, Charles; Park, Kundo; Gu, Grace X.; Ryu, Seunghwa, NPJ COMPUTATIONAL MATERIALS, v.7, no.1, 2021-09 |
| Deep learning framework for modeling the effect of VR spatial resolution in VR sickness assessment = 가상현실 멀미 측정에서 영상의 화질에 따른 영향을 모델링하는 딥러닝 프레임워크link Kim, Kihyun; Ro, Yong Man; et al, 한국과학기술원, 2019 |
| Deep learning framework for vessel trajectory prediction using auxiliary tasks and convolutional networks Shin, Yu Yol; Kim, Nam Woo; Lee, Hyeyeong; In, Soh Young; Hansen, Mark; Yoon, Yoonjin, ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, v.132, 2024-06 |
| Deep learning improves prediction of drug-drug and drug-food interactions Ryu, Jae Yong; Kim, Hyun Uk; Lee, Sang Yup, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, v.115, no.18, pp.E4304 - E4311, 2018-05 |
| Deep Learning in Biological Image and Signal Processing Meijering, Erik; Calhoun, Vince D.; Menegaz, Gloria; Miller, David J.; Ye, Jong Chul, IEEE SIGNAL PROCESSING MAGAZINE, v.39, no.2, pp.24 - 26, 2022-03 |
| Deep learning in intrusion detection perspective: overview and further challenges Kim, Kwangjo; Aminanto, Muhamad Erza, International Workshop on Big Data and Information Security (IWBIS), pp.5 - 10, IEEE, 2017-09-23 |
| Deep Learning in Intrusion Detection System: An Overview Aminanto, Erza; Kim, Kwangjo, 2016 International Research Conference on Engineering and Technology (2016 IRCET), v.0, Higher Education Forum, 2016-06 |
| DEEP LEARNING METHOD AND APPARATUS FOR AUTOMATIC UPRIGHT RECTIFICATION OF VIRTUAL REALITY CONTENT Bazin, Jean-Charles; Jung, Rae Hyuk; Lee, Seung Joon |
| Deep learning methods and architectures using multi-task learning : Performance Improvement and Image Creation = 멀티테스크 러닝을 이용한 딥러닝 기법 및 구조 : 성능향상 기법 및 이미지 창조link Yim, Junho; Kim, Junmo; et al, 한국과학기술원, 2019 |
| Deep learning methods for identifying structure and chemisorption property of materials = 머신러닝을 이용한 재료 구조 식별 및 흡착 특성 예측link Hong, Doosun; Lee, Hyuck Mo; et al, 한국과학기술원, 2022 |
| Deep learning model for diagnosing gastric mucosal lesions using endoscopic images: development, validation, and method comparison Nam, Joon Yeul; Chung, Hyung Jin; Choi, Kyu Sung; Lee, Hyuk; Kim, Tae Jun; Soh, Hosim; Kang, Eun Ae; et al, GASTROINTESTINAL ENDOSCOPY, v.95, no.2, pp.258 - +, 2022-02 |
| Deep learning model for heavy rainfall nowcasting in South Korea Oh, Seok-Geun; Son, Seok-Woo; Kim, Young-Ha; Park, Chanil; Ko, Jihoon; Shin, Kijung; Ha, Ji-Hoon; et al, WEATHER AND CLIMATE EXTREMES, v.44, 2024-06 |
| Deep learning model for immune repertoire-based cancer prediction = 면역학적 특성에 기반한 암 진단 딥러닝 모델 개발link Kim, So Yeon; 김소연; et al, 한국과학기술원, 2023 |
| Deep learning model inspired by lateral line system for underwater object detection Jeong, Taekyeong; Yoo, Janggon; Kim, Daegyoum, BIOINSPIRATION & BIOMIMETICS, v.17, no.2, 2022-01 |
| Deep learning model inspired lateral line object detection Jeong, Taekyeong; Yoo, Janggon; Kim, Daegyoum, 74th Annual Meeting of the APS Division of Fluid Dynamics, American Physical Society, 2021-11-23 |
| Deep learning models for anomaly detection and robust density estimation = 이상 탐지와 강건한 밀도 추정을 위한 딥러닝 모델link Kim, Keunseo; Kim, Heeyoung; et al, 한국과학기술원, 2022 |
| Deep Learning of Speech Features for Improved Phonetic Recognition Lee, JH; Lee Soo-Young, 12th Annual Conference of the International Speech Communication Association (Interspeech 2011), 2011-08-27 |
| Deep learning on classifying small lesions from small datasets for computer-aided diagnosis = 컴퓨터 보조 진단을 위한 소규모 자료 집합의 소형 병변 분류에서의 심층 신경망 학습link Lee, Hansang; Kim, Junmo; et al, 한국과학기술원, 2019 |
| Deep learning processors for on-device intelligence Yoo, Hoi-Jun, 30th Great Lakes Symposium on VLSI, GLSVLSI 2020, pp.1 - 8, Association for Computing Machinery, 2020-09 |
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