Zobrazeno 1 - 10
of 66
pro vyhledávání: '"Kehai Chen"'
Publikováno v:
All Earth, Vol 36, Iss 1, Pp 1-15 (2024)
The Gaofen-3 (GF-3) is a Chinese Synthetic Aperture Radar (SAR) satellite primarily designed for monitoring marine dynamic environments. Compared to spaceborne scatterometers, it can monitor sea surface wind fields with higher spatial resolution. Cur
Externí odkaz:
https://doaj.org/article/5658f919ed1f4751b4ec07e25607d4ca
Publikováno v:
IEEE Access, Vol 12, Pp 128843-128859 (2024)
Machine learning (ML) algorithms can accurately extract quantitative patterns from datasets without requiring prior knowledge, playing an increasingly crucial role in tasks such as information extraction from remotely sensed data. This study employs
Externí odkaz:
https://doaj.org/article/a77c5d3edc004594bef506653ed12a62
Autor:
Youchang Zhang, Hancheng Mei, Zhenghua Yan, Aibing Hu, Simian Wang, Changhui Feng, Kehai Chen, Wei Li, Xianhong Zhang, Panpan Ji, Guozheng Yang
Publikováno v:
Agronomy, Vol 13, Iss 5, p 1254 (2023)
Double direct seeding of cotton (with wheat or rapeseed) is a new method for cotton-growing regions in the Yangtze River Basin to adapt to the development of mechanization. It would help to reduce manual labor, optimize the amount of nitrogen fertili
Externí odkaz:
https://doaj.org/article/374b3b37810e427e9525c104f1fad526
Publikováno v:
IEEE Access, Vol 8, Pp 204494-204508 (2020)
Chinese GaoFen-3 (GF-3) synthetic aperture radar (SAR) imagery acquired in standard strip mode can capture streak features caused by wind over the sea surface, which are commonly known as wind streaks. To retrieve the sea surface wind field from a GF
Externí odkaz:
https://doaj.org/article/f1e69da79dc8425d85828adc3dd45f9c
Autor:
Xuetong Xie, Zhou Huang, Mingsen Lin, Kehai Chen, Youguo Lan, Xinzhe Yuan, Xiaomin Ye, Juhong Zou
Publikováno v:
Remote Sensing, Vol 5, Iss 12, Pp 6180-6197 (2013)
Due to the lower efficiency and the larger wind direction error of traditional algorithms, a novel integrated wind retrieval algorithm is proposed for conically scanning scatterometers. The proposed algorithm has the dual advantages of less computati
Externí odkaz:
https://doaj.org/article/b8a90d9699e644bdb5e687990860b7e6
Autor:
Kun He, Xiaoyang Chen, Chengjuan Hu, Si Zhang, Kehai Chen, Xianping Qiu, Peicheng Luo, Zhaoyang Zhu
Publikováno v:
Industrial & Engineering Chemistry Research. 62:8085-8097
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::21a5cb63102d1b8ba5846728ec0c2390
https://doi.org/10.1021/acs.iecr.3c00816
https://doi.org/10.1021/acs.iecr.3c00816
Publikováno v:
ACM Transactions on Asian and Low-Resource Language Information Processing. 22:1-14
Document-level relation extraction (DocRE) aims to extract relations among entities across multiple sentences within a document by using reasoning skills (i.e., pattern recognition, logical reasoning, coreference reasoning, etc.) related to the reaso
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::65e381c432b2fb70b1a8498ff8601f72
https://doi.org/10.1145/3572898
https://doi.org/10.1145/3572898
Publikováno v:
IEEE Transactions on Fuzzy Systems. 30:4568-4577
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d8c746ae8a3a98d41f3983ff63d3b3ff
https://doi.org/10.1109/tfuzz.2022.3167129
https://doi.org/10.1109/tfuzz.2022.3167129
Publikováno v:
Computers in Industry. 150:103945
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::110805c3b8505c324d6ce451df91a75d
https://doi.org/10.1016/j.compind.2023.103945
https://doi.org/10.1016/j.compind.2023.103945
Publikováno v:
ACM Transactions on Asian and Low-Resource Language Information Processing. 21:1-9
Recently, character information has been successfully introduced into the encoder-decoder event detection model to relieve the trigger-word mismatch problem, thus achieving impressive results in the languages without natural delimiters (i.e., Chinese
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2040ee778ee244ddf03d7d0cc587f77a
https://doi.org/10.1145/3502197
https://doi.org/10.1145/3502197