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Showing results 1 to 9 of 9

Issue Date	Title / Author(s) / Citation	File	Altmetrics
2019-01	Sensitivity and specificity evaluation of multiple neurodegenerative proteins for Creutzfeldt-Jakob disease diagnosis using a deep-learning approach Lee, Sol Moe; Hyeon, Jae Wook; Kim, Soo-Jin; Kim, Heebal; Noh, Ran; Kim, Seonghan; Lee, Yeong Seon; Kim, Su Yeon Prion, Vol.13 No.1, pp.141-150	DOI
2019-12	Estimating transpiration rates of hydroponically-grown paprika via an artificial neural network using aerial and root-zone environments and growth factors in greenhouses Nam, Du Sung; Moon, Taewon; Lee, Joon Woo; Son, Jung Eek Horticulture, Environment, and Biotechnology, Vol.60 No.6, pp.913-923	DOI
2020	디지털 이미지를 이용한 딥러닝 기반 흙의 물리적 특성 예측 김동근	view file link
2021	Development of a Methodology for Designing a Steady-state Dataset using Deep Learning : An Application to Predict NOx Emissions under Transient Conditions of a Diesel Engine 신승협	view file link
2021-01	Exploring Google Street View with deep learning for crop type mapping Yan, Yulin; Ryu, Youngryel ISPRS Journal of Photogrammetry and Remote Sensing, Vol.171, pp.278-296	DOI
2021-02	고속대량 피노타이핑 구현을 위한 시설 작물 영상처리 및 딥러닝 응용 기술 개발 양명균	link
2021-04	Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review Hwang, Sung-Wook; Sugiyama, Junji Plant Methods. 2021 Apr 28;17(1):47	view file DOI
2022-06	OptNCMiner: a deep learning approach for the discovery of natural compounds modulating disease-specific multi-targets Seo Hyun Shin; Seung Man Oh; Jung Han Yoon Park; Ki Won Lee; Hee Yang BMC Bioinformatics. Vol.23(1):218	view file DOI
2023-06	Super resolution of historic Landsat imagery using a dual generative adversarial network (GAN) model with CubeSat constellation imagery for spatially enhanced long-term vegetation monitoring Kong, Juwon; Ryu, Youngryel; Jeong, Sungchan; Zhong, Zilong; Choi, Wonseok; Kim, Jongmin; Lee, Kyungdo; Lim, Joongbin; Jang, Keunchang; Chun, Junghwa; Kim, Kyoung-Min; Houborg, Rasmus ISPRS Journal of Photogrammetry and Remote Sensing, Vol.200, pp.1-23	DOI

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