Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Linhui Feng"'
Publikováno v:
Frontiers in Cell and Developmental Biology, Vol 12 (2024)
Externí odkaz:
https://doaj.org/article/5dd37659509f472480107476f51da22a
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 11, Iss 8, p 429 (2022)
Evaluating park equity can help guide the advancement of sustainable and equitable space policies. Previous studies have mainly considered accessibility when evaluating park equity while ignoring the selectivity and convenience of entering parks and
Externí odkaz:
https://doaj.org/article/77576a4d53944282bedb31f5a046fb18
Publikováno v:
IEEE Transactions on Big Data. :1-15
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ead80b3107794effbab405c7a2be0dad
https://doi.org/10.1109/tbdata.2023.3278977
https://doi.org/10.1109/tbdata.2023.3278977
Publikováno v:
Journal of Agricultural and Food Chemistry. 70:9095-9105
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa090cb1fb241f32a7beeed474f21321
https://doi.org/10.1021/acs.jafc.2c02949
https://doi.org/10.1021/acs.jafc.2c02949
Autor:
Xiaoming Zhang, Yu Junhe, Yun Zhai, Heping Cui, Linhui Feng, Pusen Chen, Khizar Hayat, Yan Xu, Chi-Tang Ho
Publikováno v:
Trends in Food Science & Technology. 115:391-408
Background Maillard reaction occurs during food processing and storage and accounts for flavor and browning formation. As significant Maillard reaction intermediates, Amadori rearrangement products (ARPs) are key flavor and browning precursors, and t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2084131013569e8229099a159b4e6d3d
https://doi.org/10.1016/j.tifs.2021.06.055
https://doi.org/10.1016/j.tifs.2021.06.055
Publikováno v:
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence.
Temporal knowledge graph (TKG) reasoning that infers missing facts in the future is an essential and challenging task. When predicting a future event, there must be a narrative evolutionary process composed of closely related historical facts to supp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76c3d4f2c2f43eb43a613a12f7113543
https://doi.org/10.24963/ijcai.2022/284
https://doi.org/10.24963/ijcai.2022/284
Autor:
Yifu Gao, Qi Zhai, Xiangke Liao, Yu Tang, Zhigang Kan, Jianming Zheng, Dongsheng Li, Linhui Feng, Linbo Qiao, Yi Han
Publikováno v:
CIKM
Conventional deep learning-based Relation Classification (RC) methods heavily rely on large-scale training dataset and fail to generalize to unseen classes when training data is scant. This work concentrates on RC tasks in few-shot scenarios in which
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c3bea62746a5d5dff0298113ea5061b1
https://doi.org/10.1145/3459637.3482280
https://doi.org/10.1145/3459637.3482280
Publikováno v:
Mathematical Problems in Engineering, Vol 2019 (2019)
The electronic commerce (e-commerce) market is experiencing explosive growth. Millions of retail network firms compete in the virtual e-commerce market. A key aspect of online trading is emotional intelligence: these retail firms adopt emotional tact
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7047aae62f421cbfcf932e96acead01
https://doi.org/10.1155/2019/9798174
https://doi.org/10.1155/2019/9798174
Publikováno v:
Computer Science & Information Technology (CS & IT).
Recently, Chinese event detection has attracted more and more attention. As a special kind of hieroglyphics, Chinese glyphs are semantically useful but still unexplored in this task. In this paper, we propose a novel Glyph-Aware Fusion Network, named
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::136468d064ea08a8baf89cf9cb40e1d2
https://doi.org/10.5121/csit.2021.110114
https://doi.org/10.5121/csit.2021.110114
Publikováno v:
Knowledge Science, Engineering and Management ISBN: 9783030821463
KSEM
KSEM
Few-shot learning event extraction methods gain more and more attention due to their ability to handle new event types. Current few-shot learning studies mainly focus on English event detection, which suffering from error propagation due to the ident
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::72f429b338d86f146f7e1e8883b926ad
https://doi.org/10.1007/978-3-030-82147-0_7
https://doi.org/10.1007/978-3-030-82147-0_7
