Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Yijun Duan"'
Autor:
Yijun Duan, Xin Liu, Adam Jatowt, Chenyi Zhuang, Hai-Tao Yu, Steven Lynden, Kyoung-Sook Kim, Akiyoshi Matono
Publikováno v:
IEEE Access, Vol 10, Pp 73879-73892 (2022)
Actionable knowledge graph (AKG), a specialized version of knowledge graph, was proposed recently to represent, analyze, and predict human action, thus facilitating deeper understanding of human action by robots. However, the automatic construction o
Externí odkaz:
https://doaj.org/article/42b3309508464beeb311f02919acf547
Autor:
Yangyang Gao, Qinghai Hu, Sequoia I. Leuba, Le Jia, Hongyi Wang, Xiaojie Huang, Yaokai Chen, Hui Wang, Jing Zhang, Zhenxing Chu, Lukun Zhang, Zixin Wang, Hong Shang, Junjie Xu, CROPrEP Study Team, Xiaoqing He, Yao Li, Fang Zhao, Yijun Duan, Rui Li, Shangcao Li, Hang Li, Zhili Hu, Rantong Bao, Sitong Cui, Zhaozhen Liu, Zehao Ye, Xiaoyun Shi
Publikováno v:
Frontiers in Medicine, Vol 9 (2022)
BackgroundThe coronavirus disease (COVID-19) pandemic has impacted HIV prevention strategies globally. However, changes in pre-exposure prophylaxis (PrEP) adherence and HIV-related behaviors, and their associations with medication adherence among men
Externí odkaz:
https://doaj.org/article/00c67954d8c941628e40fefc94285430
Publikováno v:
Data Science and Engineering, Vol 4, Iss 4, Pp 336-351 (2019)
Abstract Knowledge of entity histories is often necessary for comprehensive understanding and characterization of entities. Yet, the analysis of an entity’s history is often most meaningful when carried out in comparison with the histories of other
Externí odkaz:
https://doaj.org/article/f9d8814cc2bf430597d76b7e8a9cdd11
Publikováno v:
Data Science and Engineering, Vol 4, Iss 3, Pp 208-222 (2019)
Abstract We propose a novel way of utilizing and accessing information stored in news archives as well as a new style of investigating the history. Our idea is to automatically generate similar entity pairs given two sets of entities, one from the pa
Externí odkaz:
https://doaj.org/article/76306a8fb7124d60b74243a67f0940b5
Autor:
Yijun Duan, Xin Liu, Adam Jatowt, Hai-tao Yu, Steven Lynden, Kyoung-Sook Kim, Akiyoshi Matono
Publikováno v:
Remote Sensing, Vol 14, Iss 18, p 4479 (2022)
In many real-world networks of interest in the field of remote sensing (e.g., public transport networks), nodes are associated with multiple labels, and node classes are imbalanced; that is, some classes have significantly fewer samples than others.
Externí odkaz:
https://doaj.org/article/4733d0722ddf46539cf6a084ee317eb8
Autor:
Yijun Duan, Xin Liu, Adam Jatowt, Hai-tao Yu, Steven Lynden, Kyoung-Sook Kim, Akiyoshi Matono
Publikováno v:
Remote Sensing, Vol 14, Iss 14, p 3295 (2022)
Deep learning algorithms have seen a massive rise in popularity for remote sensing over the past few years. Recently, studies on applying deep learning techniques to graph data in remote sensing (e.g., public transport networks) have been conducted.
Externí odkaz:
https://doaj.org/article/00b46418a6694fa1bdabedaa52f71e7e
Autor:
Yijun Duan, Xin Liu, Adam Jatowt, Hai-tao Yu, Steven Lynden, Kyoung-Sook Kim, Akiyoshi Matono
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783031263897
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9fe22870ccaf8571a6bfeeb927c254da
https://doi.org/10.1007/978-3-031-26390-3_2
https://doi.org/10.1007/978-3-031-26390-3_2
Publikováno v:
The 11th International Symposium on Information and Communication Technology.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::44c8b01c3c9d1a71f8862c91ffe3e032
https://doi.org/10.1145/3568562.3568644
https://doi.org/10.1145/3568562.3568644
Autor:
Yijun Duan, Xin Liu, Adam Jatowt, Hai-tao Yu, Steven Lynden, Kyoung-Sook Kim, Akiyoshi Matono
Publikováno v:
2022 International Joint Conference on Neural Networks (IJCNN).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::83e9dcfb05b5e6635186b02c254a324e
https://doi.org/10.1109/ijcnn55064.2022.9892598
https://doi.org/10.1109/ijcnn55064.2022.9892598
Publikováno v:
Journal of Applied Polymer Science. 139
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8dee06fe04299fd225563451377cb32b
https://doi.org/10.1002/app.52743
https://doi.org/10.1002/app.52743