Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Taegyun Jeon"'
Autor:
Heechul Jung, Taegyun Jeon
Publikováno v:
Electronics Letters, Vol 57, Iss 6, Pp 249-251 (2021)
Abstract This letter presents a new self‐supervised learning approach based on randomised layers for remote sensing. Our method is basically based on the Tile2Vec approach, which is one of the state‐of‐the‐art self‐supervised learning appro
Externí odkaz:
https://doaj.org/article/3638511d306f4793af1c8f9ca6e1570e
Publikováno v:
Remote Sensing, Vol 13, Iss 18, p 3627 (2021)
Quantitative precipitation prediction is essential for managing water-related disasters, including floods, landslides, tsunamis, and droughts. Recent advances in data-driven approaches using deep learning techniques provide improved precipitation now
Externí odkaz:
https://doaj.org/article/bf4e2722079b46d3b8d7622eb2b12420
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 19:1-5
Road extraction from very high resolution (VHR) satellite images is one of the most important topics in the field of remote sensing. In this letter, we propose an efficient nonlocal LinkNet with nonlocal blocks (NLBs) that can grasp relations between
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::21c2a3835a9717e942255e17da277d57
https://doi.org/10.1109/lgrs.2021.3050477
https://doi.org/10.1109/lgrs.2021.3050477
Autor:
Taegyun Jeon, Heechul Jung
Publikováno v:
Electronics Letters, Vol 57, Iss 6, Pp 249-251 (2021)
This letter presents a new self‐supervised learning approach based on randomised layers for remote sensing. Our method is basically based on the Tile2Vec approach, which is one of the state‐of‐the‐art self‐supervised learning approaches for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1133c72ba630a9496ea84cd46d09570b
https://doaj.org/article/3638511d306f4793af1c8f9ca6e1570e
https://doaj.org/article/3638511d306f4793af1c8f9ca6e1570e
Publikováno v:
IGARSS
Recent advances in deep learning approaches show the excellent possibility for precipitation nowcasting. The data-driven weather forecasting method provides observation-based forecasting products. This study introduces the dataset, named RAIN-F (Rada
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f10fdb3d1ecc5f1b9b98ec5f9830afb1
https://doi.org/10.1109/igarss47720.2021.9555094
https://doi.org/10.1109/igarss47720.2021.9555094
Autor:
Minyoung Back, Taegyun Jeon
Publikováno v:
IGARSS
Monitoring oil storage states with observing oil tanks provides significant indicators in terms of economics, finance and trade. Crude oil is usually stored in floating roof tanks due to the chemical properties of the reservoir. Through the geometry
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f755b460862df28730263108538d57ba
https://doi.org/10.1109/igarss39084.2020.9323501
https://doi.org/10.1109/igarss39084.2020.9323501
Autor:
Jing Liu, Yukai Shi, C. V. Jiji, Tong Yang, Mykola Mykhailych, Junyeop Lee, Gwantae Kim, Zhipeng Luo, Yandong Guo, Jiahao Wu, Liang Lin, Shengchen Zhu, Haoyu Zhong, Zhenyu Xu, Fu Li, Fuzhi Yang, JaeHyun Baek, Jong Chul Ye, Jinjia Peng, Densen Puthussery, Thomas S. Huang, Taizhang Shang, Wenhao Wu, Kai Zhang, Zhi Jin, Dongliang He, Jaihyun Park, Jeongki Min, Radu Timofte, Jungki Min, Chao Li, Kanghyu Lee, Sejong Yang, Chenming Shang, P. S. Hrishikesh, Huibing Wang, Qiuju Dai, Norimichi Ukita, Yifu Chen, Takeru Ooba, Zhijing Yang, Yuehan Yao, Jiande Jiang, Seon Joo Kim, Kazutoshi Akita, Xinbo Gao, Shuhang Gu, Xiaojun Yang, Huanrong Zhang, Kwangjin Yoon, Taegyun Jeon, Jianwei Li, Jianlong Fu, Huan Yang, Younghyun Jo, Wen Lu, Lin Zha, Byung-Hoon Kim, Bokyeung Lee, Tongtong Zhao, Shilei Wen, Ding Yukang, Yuchen Fan
Publikováno v:
CVPR Workshops
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results. The challenge task was to super-resolve an input image with a magnification factor 16 based on a set of prior examples of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6337c2c4eebd8824122f4c78906425f
Publikováno v:
ICCV Workshops
Saliency Map, the gradient of the score function with respect to the input, is the most basic technique for interpreting deep neural network decisions. However, saliency maps are often visually noisy. Although several hypotheses were proposed to acco
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d310eecd3394e85dfb7104c9d92e05dc
https://doi.org/10.1109/iccvw.2019.00510
https://doi.org/10.1109/iccvw.2019.00510
Publikováno v:
ICCV Workshops
We propose Deep Closed-Form Subspace Clustering (DCFSC), a new embarrassingly simple model for subspace clustering with learning non-linear mapping. Compared with the previous deep subspace clustering (DSC) techniques, our DCFSC does not have any par
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ae24b57f2e3083aa84b84706069e46c
http://arxiv.org/abs/1908.09419
http://arxiv.org/abs/1908.09419
Autor:
Taegyun Jeon1, Jongmin Yu1, Witold Pedrycz2,3,4, Moongu Jeon1, Boreom Lee5, Byeongcheol Lee1 byeong@gist.ac.kr, Jeon, Taegyun1 (AUTHOR), Yu, Jongmin1 (AUTHOR), Pedrycz, Witold3,4,6 (AUTHOR), Jeon, Moongu1 (AUTHOR), Lee, Boreom5 (AUTHOR), Lee, Byeongcheol1 (AUTHOR)
Publikováno v:
BioMedical Engineering OnLine. 1/15/2016, Vol. 15, p1-14. 14p.