Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Fengyuan Jiao"'
Autor:
Yaqiong Qin, Gengxu Zhou, Fengyuan Jiao, Chuan Cheng, Chi Meng, Lingjie Wang, Shengping Wu, Cailiang Fan, Jixiang Li, Bo Zhou, Yuefeng Chu, Hanwei Jiao
Publikováno v:
Frontiers in Cellular and Infection Microbiology, Vol 14 (2024)
Brucellosis is a serious zoonosis caused by Brucella spp. infection, which not only seriously jeopardizes the health of humans and mammals, but also causes huge economic losses to the livestock industry. Brucella is a Gram-negative intracellular bact
Externí odkaz:
https://doaj.org/article/075b050edb2a4d2db77bb1c2d77bb50b
Autor:
Xueqiang Shi, Jiarui Zhang, Yuanbo Zhang, Yutao Zhang, Yue Zhao, Kaiyuan Sun, Shihao Li, Yanwu Yu, Fengyuan Jiao, Weiguo Cao
Publikováno v:
Case Studies in Thermal Engineering, Vol 60, Iss , Pp 104829- (2024)
To study combustion and extinction characteristics of flames perturbed by acoustic waves, the evolution of the shape of the pool fire, mass loss rate (ma′) of fuel, and mechanisms of extinction of the flames under acoustic perturbations were studie
Externí odkaz:
https://doaj.org/article/838561265f764bfba0429521fdbb6f67
Autor:
Fengyuan Jiao, Yu Zhao, Gengxu Zhou, Chi Meng, Lingjie Wang, Shengping Wu, Jixiang Li, Liting Cao, Bo Zhou, Yichen Luo, Hanwei Jiao
Publikováno v:
Microorganisms, Vol 12, Iss 7, p 1405 (2024)
Hepatitis E (Hepatitis E, HE) is an acute and chronic infectious hepatitis caused by hepatitis E virus (Hepatitis E Virus, HEV) infection, which is responsible for most acute hepatitis in the world and is a significant public health problem. The path
Externí odkaz:
https://doaj.org/article/2628372dda4244e3837912e235fee999
Autor:
Fengyuan Jiao, Zhiguo Gui, Kunpeng Li, Hong Shangguang, Yanling Wang, Yi Liu, Pengcheng Zhang
Publikováno v:
IEEE Access, Vol 9, Pp 71091-71103 (2021)
Convolutional neural network (CNN)-based deep learning techniques have enjoyed many successful applications in the field of medical imaging. However, the complicated between-manifold projection from the projection domain to the spatial domain hinders
Externí odkaz:
https://doaj.org/article/4445d5d6b1ae4618a0c3a8ef28587322
Autor:
Fengyuan Jiao, Huarong Zhang, Wenjuan Li, Yuxin Zhao, Jiaxin Guo, Xin Zhang, Weiguo Cao, Yun Zhang
Publikováno v:
International Journal of Hydrogen Energy. 47:22261-22272
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3b2396eddbac888fb16f528899bc10e5
https://doi.org/10.1016/j.ijhydene.2022.05.017
https://doi.org/10.1016/j.ijhydene.2022.05.017
Autor:
Weiguo Cao, Zhuanghong Zhou, Wen Zhou, Siyu Xu, Qiuping Xiao, Wei Cao, Fengyuan Jiao, Yun Zhang, Shuo Yu, Sen Xu
Publikováno v:
International Journal of Hydrogen Energy. 47:10420-10430
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bbdb191a85c83c5970c3ec0601b8b8fa
https://doi.org/10.1016/j.ijhydene.2022.01.082
https://doi.org/10.1016/j.ijhydene.2022.01.082
Autor:
Weiguo Cao, Xin Zhang, Yue Jia, Zhuanghong Zhou, Wenjuan Li, Qiuping Xiao, Sen Xu, Fengyuan Jiao, Fengqi Zhao, Siyu Xu, Yun Zhang
Publikováno v:
Combustion and Flame. 254:112842
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa63e81cafeb09d84e51843d5cc87668
https://doi.org/10.1016/j.combustflame.2023.112842
https://doi.org/10.1016/j.combustflame.2023.112842
Publikováno v:
Signal, Image and Video Processing. 15:1907-1915
Utilization of lower dose to generate CT images (LDCT) can reduce X-ray radiation damage to human body, but the resulting noise and artifacts will hinder its applications for clinical diagnosis. In order to solve the difficulty in separating the imag
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7cc25e5a91b3eee980753f7098738615
https://doi.org/10.1007/s11760-021-01935-0
https://doi.org/10.1007/s11760-021-01935-0
In order to solve the problems of artifacts and noise in low-dose computed tomography ( CT ) images in clinical medical diagnosis, an improved image denoising algorithm under the architecture of generative adversarial network ( GAN ) is proposed. Fir
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::88452394d8015378fd6fa328b9b1e32f
https://doi.org/10.21203/rs.3.rs-1672475/v1
https://doi.org/10.21203/rs.3.rs-1672475/v1
Autor:
Yanling Wang, Yi Liu, Pengcheng Zhang, Zhiguo Gui, Fengyuan Jiao, Hong Shangguang, Kunpeng Li
Publikováno v:
IEEE Access, Vol 9, Pp 71091-71103 (2021)
Convolutional neural network (CNN)-based deep learning techniques have enjoyed many successful applications in the field of medical imaging. However, the complicated between-manifold projection from the projection domain to the spatial domain hinders
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::01dfcbb198a098b47c52f8f1547aa95b
https://doi.org/10.1109/access.2021.3079323
https://doi.org/10.1109/access.2021.3079323