Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Feihao Chen"'
Publikováno v:
Buildings, Vol 14, Iss 11, p 3640 (2024)
In this study, a multilayer composite rolling model consisting of a rolling wheel, a protective layer, a GCL, and a support layer was constructed by the discrete element method (DEM). Soil compaction and gravel migration, and their effects on the GCL
Externí odkaz:
https://doaj.org/article/41ea1ad84c2c4065b8cd36bee90e82cf
Autor:
Feihao Chen, Jin Yeu Tsou
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 112, Iss , Pp 102865- (2022)
Although the application of deep learning in remote sensing (RS) has achieved fruitful results, systematic research on exploring the model performance and guiding the design of new convolutional neural network (CNN) architectures is still lacking. Th
Externí odkaz:
https://doaj.org/article/dd7b14742edd4dc68e72cd29a5298da3
Autor:
Feihao Chen, Jin Yeu Tsou
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 104, Iss , Pp 102577- (2021)
Mainstream architectures of convolutional neural networks (CNNs) for image recognition follow the protocol of shrinking input data size to extract semantic information. However, poor overall accuracy (OA) may be achieved when dealing with small input
Externí odkaz:
https://doaj.org/article/65187281cbc24ed890599fc231a672fe
Autor:
Feihao Chen, Yefu Chen
Publikováno v:
Climate Research. 81:91-112
Urban climate research is essential for sustainable development. Few review papers have focused on long-term research and planning applications in China. We conducted a bibliometric review by using CiteSpace to elaborate changes in hot spots, frontie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2b3f28b534454abd69867cd4ecf176e0
https://doi.org/10.3354/cr01611
https://doi.org/10.3354/cr01611
Autor:
Jin Yeu Tsou, Feihao Chen
Publikováno v:
International Journal of Applied Earth Observation and Geoinformation. 104:102577
Mainstream architectures of convolutional neural networks (CNNs) for image recognition follow the protocol of shrinking input data size to extract semantic information. However, poor overall accuracy (OA) may be achieved when dealing with small input
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2831359d3f4bd429640b8b42e4990cd6
https://doi.org/10.1016/j.jag.2021.102577
https://doi.org/10.1016/j.jag.2021.102577
Autor:
Jin Yeu Tsou, Feihao Chen
Publikováno v:
International Journal of Oil, Gas and Coal Technology. 1:1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::adefddc96e3b4381a960687a7a3df568
https://doi.org/10.1504/ijogct.2021.10036107
https://doi.org/10.1504/ijogct.2021.10036107